Wikiversity enwikiversity https://en.wikiversity.org/wiki/Wikiversity:Main_Page MediaWiki 1.47.0-wmf.22 first-letter Media Special Talk User User talk Wikiversity Wikiversity talk File File talk MediaWiki MediaWiki talk Template Template talk Help Help talk Category Category talk School School talk Portal Portal talk Topic Topic talk Collection Collection talk Draft Draft talk TimedText TimedText talk Module Module talk Event Event talk 4 28 2835339 2834593 2026-10-01T12:42:33Z MediaWiki message delivery 983498 /* Wikidata Sitelink changes in Recent Changes and Watchlist */ new section 2835339 wikitext text/x-wiki {{Wikiversity:Colloquium/Header}} <!-- MESSAGES GO BELOW --> == Add an edit count requirement for autoconfirmed? == Currently, only waiting for four days is required for a user to become autoconfirmed. I am proposing that we include a minimum edit count of 10 edits (akin to Wikipedia) especially because of [[Special:AbuseFilter/16|a private abuse filter]], and LTAs may game autoconfirmed permissions to vandalize here. Thoughts? [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] ([[User talk:Codename Noreste|discuss]] • [[Special:Contributions/Codename Noreste|contribs]]) 23:01, 23 August 2026 (UTC) : [[Wikiversity:Autoconfirmed users]] : Are you suggesting an additional requirement? i.e., 4 days + 10 edits? : How is it adjusted? -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 03:57, 5 September 2026 (UTC) :: Yes. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 01:30, 6 September 2026 (UTC) :: @[[User:Jtneill|Jtneill]]: I said yes to your first question. As for the adjustment question, in the InitialiseSettings.php file on noc.wikimedia.org, on <code>wgAutoConfirmCount</code> is where English Wikiversity would be added as <code>'enwikiversity' => 10,</code>. Does my reply make sense? [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 18:31, 15 September 2026 (UTC) :As a newly volunteered member, it doesn't seem unreasonable to me to require a certain number of edits to establish my bona fides. [[User:Cfm490|Cfm490]] ([[User talk:Cfm490|discuss]] • [[Special:Contributions/Cfm490|contribs]]) 17:53, 5 September 2026 (UTC) :I agree that adding an edit count requirement is a reasonable expectation before the user can become autoconfirmed. [[User:IanVG|IanVG]] ([[User talk:IanVG|discuss]] • [[Special:Contributions/IanVG|contribs]]) 18:56, 6 September 2026 (UTC) :+ 1 —[[User:Atcovi|Atcovi]] [[User talk:Atcovi|(Talk]] - [[Special:Contributions/Atcovi|Contribs)]] 19:40, 6 September 2026 (UTC) :'''Weak support''' Generally reasonable, but I would caution that we should really make this clear for those instances where professors have students edit here and make it frictionless for them to get autoconfirmed status. ―[[User:Koavf|Justin (<span style="color:grey">ko'''a'''<span style="color:black">v</span>f</span>)]]<span style="color:red">❤[[User talk:Koavf|T]]☮[[Special:Contributions/Koavf|C]]☺[[Special:Emailuser/Koavf|M]]☯</span> 19:42, 6 September 2026 (UTC) : {{oppose|No support}} because I cannot see the [[Special:AbuseFilter/16|abuse filter]] cited as the primary reason and I do not know what LTAs is. I guess you don’t want support from ''ordinary'' users. ‑‑[[User:Kai Burghardt|Kays]] ([[User talk:Kai Burghardt|discuss]] • [[Special:Contributions/Kai Burghardt|contribs]]) 18:18, 14 September 2026 (UTC) ::Also some readers may be interested in this: ::* [[Wikipedia/Types of user accounts]] ::[[Special:Contributions/~2026-40514-81|~2026-40514-81]] ([[User talk:~2026-40514-81|talk]]) 19:05, 14 September 2026 (UTC) ::: An LTA means a long-term abuser, and it means someone who is usually abusive. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 20:42, 14 September 2026 (UTC) :'''Strong''' {{support}}; specially to battle LTA [[User:Mbataw|Mbataw]] ([[User talk:Mbataw|discuss]] • [[Special:Contributions/Mbataw|contribs]]) 13:17, 18 September 2026 (UTC) :{{support}}, having no edit count requirement for autoconfirmed is a bad idea in general. [[User:BooksBooksBooks3|BooksBooksBooks3]] ([[User talk:BooksBooksBooks3|discuss]] • [[Special:Contributions/BooksBooksBooks3|contribs]]) 01:43, 19 September 2026 (UTC) :Comment: I realize that it is not easy to be an admin on wikimedia projects. I realize that many admins have to deal with some VERY unpleasant personalities. But.. :Admins are not the only users who encounter harassment on wikimedia projects, big or small. Anyone who's been here as long as I have, has come across users who are not tolerated by the "community". Not necessarily because they are spammers, trollers, paid editors, LTAs , disruptive etc, but simply because they are different. :When I "edit" without logging in, I carry no baggage. I also get encouraging prompts such as this: :* This year, Wikipedia has had fewer visitors and fewer new supporters, so '''<big>your visit today means a lot</BIG>''' :Anyway, back to the topic at hand [[Wikipedia/Types of user accounts]]. I believe the section about IP editors is outdated since wikimedia now views users who are not logged-in as anonymous, and only trusted users are allowed to see their IP address (I am not clear on the details). I wonder if anyone participating here has an interest in bringing this page uptodate? [[Special:Contributions/~2026-40514-81|~2026-40514-81]] ([[User talk:~2026-40514-81|talk]]) 04:13, 22 September 2026 (UTC) : If there's some obvious things to fix, I'd say go ahead. It looks like there were several useful anonymous contributions to that page recently. -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 07:54, 22 September 2026 (UTC) :hmm [[User:Tornaiden|Tornaiden]] ([[User talk:Tornaiden|discuss]] • [[Special:Contributions/Tornaiden|contribs]]) 02:02, 27 September 2026 (UTC) == Bartending Course on Wikiversity == I recently finished the course on [[Bartending]], and while I have experience editing on Wikipedia, this is my first Wikiversity project. If any of you have the time or interest, I could use an experienced eye to see if there's anything obviously missing from the course in terms of Wikiversity administration. I'm not sure what's active, if the course should belong in an existing school, or if there's any obvious discoverability tool I haven't implemented. Any tips are welcomed, or just a thumbs up saying it looks fine would be great. [[User:Jtneill|Jtneill]] recommended I post this here in case someone wanted to include the new course under News on the [[Wikiversity:Main Page|Main Page]]. Thanks! [[User:Sabbier|Sabbier]] ([[User talk:Sabbier|discuss]] • [[Special:Contributions/Sabbier|contribs]]) 01:24, 1 September 2026 (UTC) :Wow! Fantastic work- I'm so impressed! Your work gives me inspiration on how to better organize the courses I'm working on. :) [[User:IanVG|IanVG]] ([[User talk:IanVG|discuss]] • [[Special:Contributions/IanVG|contribs]]) 21:32, 3 September 2026 (UTC) : Awesome work. I've added this course to the [[Main Page/News|main page news]]. : We could also consider for [[Wikiversity:Featured]]. -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 00:43, 5 September 2026 (UTC) ::The course [[Creating Wikiversity Courses]] is intended to provide guidance to new Wikiversity editors. I hope it is helpful and I welcome improvement suggestions. Thanks. [[User:Lbeaumont|Lbeaumont]] ([[User talk:Lbeaumont|discuss]] • [[Special:Contributions/Lbeaumont|contribs]]) 14:08, 6 September 2026 (UTC) == Writing news here == I'm bringing up this discussion again because I think it is beneficial to the project since Wikinews is gone, thank you. [[User:BigKrow|BigKrow]] ([[User talk:BigKrow|discuss]] • [[Special:Contributions/BigKrow|contribs]]) 03:17, 1 September 2026 (UTC) : Given that the community consensus here was not to replicate WikiNews within Wikiversity, I suggest thinking differently e.g., in terms of specific news-related projects you are interested in that have educational objectives that satisfy Wikiversity's mission. -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 00:46, 5 September 2026 (UTC) ::I wonder if you mean <u>Wikiversity:Main Page/News ?</u> ::If so I have just checked this page and I see it only contains news for 2026 and part of 2025, even though the history indicates it was created in the 2000-decade. If you go back and check all revisions there is a wealth of (historical?) information. [[Special:Contributions/~2026-40514-81|~2026-40514-81]] ([[User talk:~2026-40514-81|talk]]) 16:28, 13 September 2026 (UTC) ::: I didn't mean that page, but yes, its history could be reconstructed into a more accessible format. -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 21:37, 13 September 2026 (UTC) == [[Wikiversity talk:Interface administrators#My thoughts about this user group]] == As I suggested, I would like to propose allowing permanent interface administrators on English Wikiversity. My temporary interface admin rights are about to expire soon, and I will soon create a new CfIA page (and its header). We should also have a minimum of two interface administrators. Thoughts? [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 16:44, 6 September 2026 (UTC) :I am also in favor of this and we did discuss it pretty recently and came to a consensus on extending IA rights and lowering the administrative overhead, but not allowing indefinite at this juncture. From my perspective, since we discussed this so recently and nothing seems to have changed much, I personally would recommend holding off for a couple of years or until/unless there is some critical new information. Again, I would continue to support indef IA rights were it to come up again and think that at least two is also a sensible proposal. ―[[User:Koavf|Justin (<span style="color:grey">ko'''a'''<span style="color:black">v</span>f</span>)]]<span style="color:red">❤[[User talk:Koavf|T]]☮[[Special:Contributions/Koavf|C]]☺[[Special:Emailuser/Koavf|M]]☯</span> 17:32, 6 September 2026 (UTC) ::Responding to myself so that I don't derail: I would be interested/willing to be an indef IA. ―[[User:Koavf|Justin (<span style="color:grey">ko'''a'''<span style="color:black">v</span>f</span>)]]<span style="color:red">❤[[User talk:Koavf|T]]☮[[Special:Contributions/Koavf|C]]☺[[Special:Emailuser/Koavf|M]]☯</span> 17:36, 6 September 2026 (UTC) : I made [[Wikiversity:Candidates for Interface Adminship]]. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 18:24, 6 September 2026 (UTC) :: CC to @[[User:Koavf|Koavf]]. I made a request since my IA rights are about to expire. We should also hold a separate vote to allow permanent IAs here (for this policy). [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 16:55, 7 September 2026 (UTC) : @[[User:Jtneill|Jtneill]], I count at least three in favor (votes below, and Koavf agreeing), so can you close this request? Thank you. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 15:22, 24 September 2026 (UTC) === Votes === * For the record, I am creating a separate subsection for voting, whether or not we should allow permanent interface administrators. {{support}} accordingly. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 18:32, 15 September 2026 (UTC) * {{support}} [[User:PieWriter|PieWriter]] ([[User talk:PieWriter|discuss]] • [[Special:Contributions/PieWriter|contribs]]) 00:51, 18 September 2026 (UTC) == Paid part-time Administrative Officer position with WikiJournal == [[WikiJournal User Group|WikiJournal]] is an open-access, nonprofit scholarly publisher hosted on Wikiversity. It uses the wiki format to allow authors to write and develop scholarly articles directly online. Submitted articles then undergo formal academic peer review and, when accepted, are published as citable journal articles while remaining freely accessible. WikiJournal is seeking expressions of interest in a new part-time '''Administrative Officer''' position. The officer would support the project's day-to-day organizational work, including: * Setting up and administering a system for tracking contractor hours and issuing payments. * Coordinating the contracting, onboarding, timekeeping and payment of technical editors and other contractors. * Maintaining financial, contractor and administrative records. * Assisting with grant administration, budget tracking and reporting. * Following up on board action items, deadlines and recurring obligations. * Supporting recruitment and other operational tasks as needed. This is a remote, flexibly scheduled contractor role averaging approximately '''6 hours per week'''. Compensation is proposed at '''US$25 per hour''', with up to approximately '''320 hours (US$8,000) available over the year'''. Applicants may be based internationally, although appointment will depend on WikiJournal being able to establish a practical and legally appropriate contracting and payment arrangement in the applicant's country of residence. Relevant experience may include administrative organization, bookkeeping or financial administration, contractor or personnel coordination, nonprofit or grant administration, Wikimedia participation, academic publishing, and open-access work. Applicants are not expected to have experience in every area. For the complete role description and further details, see [[WikiJournal User Group/Administrative officer]]. Those interested should reply in the '''[[Talk:WikiJournal User Group#Call for interest: Administrative Officer|Call for interest: Administrative Officer]]''' discussion by '''30 September 2026''', briefly describing their relevant experience, any connection to WikiJournal or related communities, and their general availability. Expressions of interest received later may still be considered if the position has not been filled. Recommendations of potentially suitable candidates are also welcome. [[User:Mikael Häggström|Mikael Häggström]] ([[User talk:Mikael Häggström|discuss]] • [[Special:Contributions/Mikael Häggström|contribs]]) 20:00, 10 September 2026 (UTC) == Server switch - Your wiki will be read-only for a short time soon == <section begin="server-switch"/><div class="plainlinks"> [[:m:Special:MyLanguage/Tech/Server switch|Read this message in another language]] • [https://meta.wikimedia.org/w/index.php?title=Special:Translate&group=page-Tech%2FServer+switch&language=&action=page&filter= {{int:please-translate}}] The [[foundation:|Wikimedia Foundation]] will switch the traffic between its data centers. This will make sure that Wikipedia and the other Wikimedia wikis can stay online even after a disaster. All traffic will switch on '''{{#time:j xg|2026-09-23|en}}'''. The switch will start at '''[https://zonestamp.toolforge.org/{{#time:U|2026-09-23T14:00|en}} {{#time:H:i e|2026-09-23T14:00}}]'''. Unfortunately, because of some limitations in [[mw:Special:MyLanguage/Manual:What is MediaWiki?|MediaWiki]], all editing must stop while the switch is made. We apologize for this disruption, and we are working to minimize it in the future. A banner will be displayed on all wikis 30 minutes before this operation happens. This banner will remain visible until the end of the operation. You can contribute to the [https://meta.wikimedia.org/w/index.php?title=Special%3ATranslate&group=Centralnotice-tgroup-read_only_banner&task=view&language=&filter=&action=translate translation or proofreading] of this banner text. '''You will be able to read, but not edit, all wikis for a short period of time.''' * You will not be able to edit for up to an hour on {{#time:l j xg Y|2026-09-23|en}}. * If you try to edit or save during these times, you will see an error message. We hope that no edits will be lost during these minutes, but we can't guarantee it. If you see the error message, then please wait until everything is back to normal. Then you should be able to save your edit. But, we recommend that you make a copy of your changes first, just in case. ''Other effects'': * Background jobs will be slower and some may be dropped. Red links might not be updated as quickly as normal. If you create an article that is already linked somewhere else, the link will stay red longer than usual. Some long-running scripts will have to be stopped. * We expect the code deployments to happen as any other week. However, some case-by-case code freezes could punctually happen if the operation require them afterwards. * [[mw:Special:MyLanguage/GitLab|GitLab]] will be unavailable for about 90 minutes. This project may be postponed if necessary. You can [[wikitech:Switch_Datacenter|read the schedule at wikitech.wikimedia.org]]. Any changes will be announced in the schedule. '''Please share this information with your community.'''</div><section end="server-switch"/> [[m:user:Trizek (WMF)|Trizek (WMF)]] 12:58, 15 September 2026 (UTC) <!-- Message sent by User:Trizek (WMF)@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Distribution_list/Non-Technical_Village_Pumps_distribution_list&oldid=30513874 --> == Your feedback wanted: Remove ''(Language link added:) and similar'' edits from Special:RecentChanges == ''(Apologies for posting in English. You can help by translating it)'' Hello, I’m Danny from [[:en:w:Wikimedia_Deutschland|Wikimedia Deutschland’s]] [[m:Wikidata_For_Wikimedia_Projects|Wikidata For Wikimedia Projects]] team.<br/> We have been investigating and examining how Wikidata’s use in the [[Special:RecentChanges]] and [[Special:Watchlist]] pages can be made to be more useful, or less ‘noisy’ (fewer edits that have little value to the reader). We are currently exploring to make a change in the volume and the type of Wikidata edits that appear in these pages, and '''we need your feedback''' to help us ensure this is a positive change for the Wikis and won’t disrupt your workflows.<br/> Language links are also known as sitelinks or interlanguage links and describe when a Wikidata item is connected to a Wiki, adding it to the language dropdown tool for other connected Wikis. [[File:Types of Lang Link changes.png|x350px|frame|A variety of "Language Link" edits as seen in the Recent Changes feed]] The request for feedback is whether you support the removal of these language link edits from the Recent Changes and Watchlist feed, or would you oppose such a change and if so, why? Please share you thoughts on the dedicated '''[[m:Talk:Wikidata_For_Wikimedia_Projects/Clearer_Wikidata_Edit_Summaries/Hide_Language_Link_edits|metawiki Talk page]]'''. Further information about this change: [[m:Wikidata_For_Wikimedia_Projects/Clearer_Wikidata_Edit_Summaries/Hide_Language_Link_edits|m:Wikidata_For_Wikimedia_Projects/Hide_Language_Link_edits]] Thank you for any participation or feedback you give, -- [[m:User:Danny_Benjafield_(WMDE)|User:Danny Benjafield (WMDE)]] 12:23, 25 September 2026 (UTC) <!-- Message sent by User:Danny Benjafield (WMDE)@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=User:Danny_Benjafield_(WMDE)/MassMessage_test_list&oldid=31080985 --> == Wikidata Sitelink changes in Recent Changes and Watchlist == ''(Apologies for cross-posting in English, translating it will help spread the message)'' Editors on group 1 wikis, including Wikiquote, Wikibooks, Wikiversity, Wikivoyage, and Wikisource, will no longer see notifications on [[Special:RecentChanges|Recent Changes]] and [[Special:Watchlist|Watchlist]] when a link to ''another'' language version of a page is added, removed, or changed in its Wikidata item. This change will begin on '''October 5 at 07:00 UTC''' as a two-week trial to reduce high-volume, low-value notifications and make higher-value changes easier to identify. Editors who rely on these notifications should be aware of the change and can share feedback or concerns on the [[m:Wikidata For Wikimedia Projects/Clearer Wikidata Edit Summaries/Hide Language Link edits|project]] or [[m:Talk:Wikidata_For_Wikimedia_Projects/Clearer_Wikidata_Edit_Summaries/Hide_Language_Link_edits|talk page]].<br/>Please reach out if you have any questions, thank you! -- [[User:Danny_Benjafield_(WMDE)|Danny Benjafield (WMDE)]] ([[User_talk:Danny_Benjafield_(WMDE)|talk]]) sent via [[User:MediaWiki message delivery|MediaWiki message delivery]] ([[User talk:MediaWiki message delivery|discuss]] • [[Special:Contributions/MediaWiki message delivery|contribs]]) 12:42, 1 October 2026 (UTC) <!-- Message sent by User:Danny Benjafield (WMDE)@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=User:Danny_Benjafield_(WMDE)/MassMessage_test_list&oldid=31106967 --> e746js8pvn98qne5pc4b1cdeood89lp 2835385 2835339 2026-10-01T20:53:04Z Codename Noreste 2969951 /* Demote Wikiversity:CheckUser policy? */ new topic ([[mw:c:Special:MyLanguage/User:JWBTH/CD|CD]]) 2835385 wikitext text/x-wiki {{Wikiversity:Colloquium/Header}} <!-- MESSAGES GO BELOW --> == Add an edit count requirement for autoconfirmed? == Currently, only waiting for four days is required for a user to become autoconfirmed. I am proposing that we include a minimum edit count of 10 edits (akin to Wikipedia) especially because of [[Special:AbuseFilter/16|a private abuse filter]], and LTAs may game autoconfirmed permissions to vandalize here. Thoughts? [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] ([[User talk:Codename Noreste|discuss]] • [[Special:Contributions/Codename Noreste|contribs]]) 23:01, 23 August 2026 (UTC) : [[Wikiversity:Autoconfirmed users]] : Are you suggesting an additional requirement? i.e., 4 days + 10 edits? : How is it adjusted? -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 03:57, 5 September 2026 (UTC) :: Yes. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 01:30, 6 September 2026 (UTC) :: @[[User:Jtneill|Jtneill]]: I said yes to your first question. As for the adjustment question, in the InitialiseSettings.php file on noc.wikimedia.org, on <code>wgAutoConfirmCount</code> is where English Wikiversity would be added as <code>'enwikiversity' => 10,</code>. Does my reply make sense? [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 18:31, 15 September 2026 (UTC) :As a newly volunteered member, it doesn't seem unreasonable to me to require a certain number of edits to establish my bona fides. [[User:Cfm490|Cfm490]] ([[User talk:Cfm490|discuss]] • [[Special:Contributions/Cfm490|contribs]]) 17:53, 5 September 2026 (UTC) :I agree that adding an edit count requirement is a reasonable expectation before the user can become autoconfirmed. [[User:IanVG|IanVG]] ([[User talk:IanVG|discuss]] • [[Special:Contributions/IanVG|contribs]]) 18:56, 6 September 2026 (UTC) :+ 1 —[[User:Atcovi|Atcovi]] [[User talk:Atcovi|(Talk]] - [[Special:Contributions/Atcovi|Contribs)]] 19:40, 6 September 2026 (UTC) :'''Weak support''' Generally reasonable, but I would caution that we should really make this clear for those instances where professors have students edit here and make it frictionless for them to get autoconfirmed status. ―[[User:Koavf|Justin (<span style="color:grey">ko'''a'''<span style="color:black">v</span>f</span>)]]<span style="color:red">❤[[User talk:Koavf|T]]☮[[Special:Contributions/Koavf|C]]☺[[Special:Emailuser/Koavf|M]]☯</span> 19:42, 6 September 2026 (UTC) : {{oppose|No support}} because I cannot see the [[Special:AbuseFilter/16|abuse filter]] cited as the primary reason and I do not know what LTAs is. I guess you don’t want support from ''ordinary'' users. ‑‑[[User:Kai Burghardt|Kays]] ([[User talk:Kai Burghardt|discuss]] • [[Special:Contributions/Kai Burghardt|contribs]]) 18:18, 14 September 2026 (UTC) ::Also some readers may be interested in this: ::* [[Wikipedia/Types of user accounts]] ::[[Special:Contributions/~2026-40514-81|~2026-40514-81]] ([[User talk:~2026-40514-81|talk]]) 19:05, 14 September 2026 (UTC) ::: An LTA means a long-term abuser, and it means someone who is usually abusive. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 20:42, 14 September 2026 (UTC) :'''Strong''' {{support}}; specially to battle LTA [[User:Mbataw|Mbataw]] ([[User talk:Mbataw|discuss]] • [[Special:Contributions/Mbataw|contribs]]) 13:17, 18 September 2026 (UTC) :{{support}}, having no edit count requirement for autoconfirmed is a bad idea in general. [[User:BooksBooksBooks3|BooksBooksBooks3]] ([[User talk:BooksBooksBooks3|discuss]] • [[Special:Contributions/BooksBooksBooks3|contribs]]) 01:43, 19 September 2026 (UTC) :Comment: I realize that it is not easy to be an admin on wikimedia projects. I realize that many admins have to deal with some VERY unpleasant personalities. But.. :Admins are not the only users who encounter harassment on wikimedia projects, big or small. Anyone who's been here as long as I have, has come across users who are not tolerated by the "community". Not necessarily because they are spammers, trollers, paid editors, LTAs , disruptive etc, but simply because they are different. :When I "edit" without logging in, I carry no baggage. I also get encouraging prompts such as this: :* This year, Wikipedia has had fewer visitors and fewer new supporters, so '''<big>your visit today means a lot</BIG>''' :Anyway, back to the topic at hand [[Wikipedia/Types of user accounts]]. I believe the section about IP editors is outdated since wikimedia now views users who are not logged-in as anonymous, and only trusted users are allowed to see their IP address (I am not clear on the details). I wonder if anyone participating here has an interest in bringing this page uptodate? [[Special:Contributions/~2026-40514-81|~2026-40514-81]] ([[User talk:~2026-40514-81|talk]]) 04:13, 22 September 2026 (UTC) : If there's some obvious things to fix, I'd say go ahead. It looks like there were several useful anonymous contributions to that page recently. -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 07:54, 22 September 2026 (UTC) :hmm [[User:Tornaiden|Tornaiden]] ([[User talk:Tornaiden|discuss]] • [[Special:Contributions/Tornaiden|contribs]]) 02:02, 27 September 2026 (UTC) == Bartending Course on Wikiversity == I recently finished the course on [[Bartending]], and while I have experience editing on Wikipedia, this is my first Wikiversity project. If any of you have the time or interest, I could use an experienced eye to see if there's anything obviously missing from the course in terms of Wikiversity administration. I'm not sure what's active, if the course should belong in an existing school, or if there's any obvious discoverability tool I haven't implemented. Any tips are welcomed, or just a thumbs up saying it looks fine would be great. [[User:Jtneill|Jtneill]] recommended I post this here in case someone wanted to include the new course under News on the [[Wikiversity:Main Page|Main Page]]. Thanks! [[User:Sabbier|Sabbier]] ([[User talk:Sabbier|discuss]] • [[Special:Contributions/Sabbier|contribs]]) 01:24, 1 September 2026 (UTC) :Wow! Fantastic work- I'm so impressed! Your work gives me inspiration on how to better organize the courses I'm working on. :) [[User:IanVG|IanVG]] ([[User talk:IanVG|discuss]] • [[Special:Contributions/IanVG|contribs]]) 21:32, 3 September 2026 (UTC) : Awesome work. I've added this course to the [[Main Page/News|main page news]]. : We could also consider for [[Wikiversity:Featured]]. -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 00:43, 5 September 2026 (UTC) ::The course [[Creating Wikiversity Courses]] is intended to provide guidance to new Wikiversity editors. I hope it is helpful and I welcome improvement suggestions. Thanks. [[User:Lbeaumont|Lbeaumont]] ([[User talk:Lbeaumont|discuss]] • [[Special:Contributions/Lbeaumont|contribs]]) 14:08, 6 September 2026 (UTC) == Writing news here == I'm bringing up this discussion again because I think it is beneficial to the project since Wikinews is gone, thank you. [[User:BigKrow|BigKrow]] ([[User talk:BigKrow|discuss]] • [[Special:Contributions/BigKrow|contribs]]) 03:17, 1 September 2026 (UTC) : Given that the community consensus here was not to replicate WikiNews within Wikiversity, I suggest thinking differently e.g., in terms of specific news-related projects you are interested in that have educational objectives that satisfy Wikiversity's mission. -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 00:46, 5 September 2026 (UTC) ::I wonder if you mean <u>Wikiversity:Main Page/News ?</u> ::If so I have just checked this page and I see it only contains news for 2026 and part of 2025, even though the history indicates it was created in the 2000-decade. If you go back and check all revisions there is a wealth of (historical?) information. [[Special:Contributions/~2026-40514-81|~2026-40514-81]] ([[User talk:~2026-40514-81|talk]]) 16:28, 13 September 2026 (UTC) ::: I didn't mean that page, but yes, its history could be reconstructed into a more accessible format. -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 21:37, 13 September 2026 (UTC) == [[Wikiversity talk:Interface administrators#My thoughts about this user group]] == As I suggested, I would like to propose allowing permanent interface administrators on English Wikiversity. My temporary interface admin rights are about to expire soon, and I will soon create a new CfIA page (and its header). We should also have a minimum of two interface administrators. Thoughts? [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 16:44, 6 September 2026 (UTC) :I am also in favor of this and we did discuss it pretty recently and came to a consensus on extending IA rights and lowering the administrative overhead, but not allowing indefinite at this juncture. From my perspective, since we discussed this so recently and nothing seems to have changed much, I personally would recommend holding off for a couple of years or until/unless there is some critical new information. Again, I would continue to support indef IA rights were it to come up again and think that at least two is also a sensible proposal. ―[[User:Koavf|Justin (<span style="color:grey">ko'''a'''<span style="color:black">v</span>f</span>)]]<span style="color:red">❤[[User talk:Koavf|T]]☮[[Special:Contributions/Koavf|C]]☺[[Special:Emailuser/Koavf|M]]☯</span> 17:32, 6 September 2026 (UTC) ::Responding to myself so that I don't derail: I would be interested/willing to be an indef IA. ―[[User:Koavf|Justin (<span style="color:grey">ko'''a'''<span style="color:black">v</span>f</span>)]]<span style="color:red">❤[[User talk:Koavf|T]]☮[[Special:Contributions/Koavf|C]]☺[[Special:Emailuser/Koavf|M]]☯</span> 17:36, 6 September 2026 (UTC) : I made [[Wikiversity:Candidates for Interface Adminship]]. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 18:24, 6 September 2026 (UTC) :: CC to @[[User:Koavf|Koavf]]. I made a request since my IA rights are about to expire. We should also hold a separate vote to allow permanent IAs here (for this policy). [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 16:55, 7 September 2026 (UTC) : @[[User:Jtneill|Jtneill]], I count at least three in favor (votes below, and Koavf agreeing), so can you close this request? Thank you. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 15:22, 24 September 2026 (UTC) === Votes === * For the record, I am creating a separate subsection for voting, whether or not we should allow permanent interface administrators. {{support}} accordingly. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 18:32, 15 September 2026 (UTC) * {{support}} [[User:PieWriter|PieWriter]] ([[User talk:PieWriter|discuss]] • [[Special:Contributions/PieWriter|contribs]]) 00:51, 18 September 2026 (UTC) == Paid part-time Administrative Officer position with WikiJournal == [[WikiJournal User Group|WikiJournal]] is an open-access, nonprofit scholarly publisher hosted on Wikiversity. It uses the wiki format to allow authors to write and develop scholarly articles directly online. Submitted articles then undergo formal academic peer review and, when accepted, are published as citable journal articles while remaining freely accessible. WikiJournal is seeking expressions of interest in a new part-time '''Administrative Officer''' position. The officer would support the project's day-to-day organizational work, including: * Setting up and administering a system for tracking contractor hours and issuing payments. * Coordinating the contracting, onboarding, timekeeping and payment of technical editors and other contractors. * Maintaining financial, contractor and administrative records. * Assisting with grant administration, budget tracking and reporting. * Following up on board action items, deadlines and recurring obligations. * Supporting recruitment and other operational tasks as needed. This is a remote, flexibly scheduled contractor role averaging approximately '''6 hours per week'''. Compensation is proposed at '''US$25 per hour''', with up to approximately '''320 hours (US$8,000) available over the year'''. Applicants may be based internationally, although appointment will depend on WikiJournal being able to establish a practical and legally appropriate contracting and payment arrangement in the applicant's country of residence. Relevant experience may include administrative organization, bookkeeping or financial administration, contractor or personnel coordination, nonprofit or grant administration, Wikimedia participation, academic publishing, and open-access work. Applicants are not expected to have experience in every area. For the complete role description and further details, see [[WikiJournal User Group/Administrative officer]]. Those interested should reply in the '''[[Talk:WikiJournal User Group#Call for interest: Administrative Officer|Call for interest: Administrative Officer]]''' discussion by '''30 September 2026''', briefly describing their relevant experience, any connection to WikiJournal or related communities, and their general availability. Expressions of interest received later may still be considered if the position has not been filled. Recommendations of potentially suitable candidates are also welcome. [[User:Mikael Häggström|Mikael Häggström]] ([[User talk:Mikael Häggström|discuss]] • [[Special:Contributions/Mikael Häggström|contribs]]) 20:00, 10 September 2026 (UTC) == Server switch - Your wiki will be read-only for a short time soon == <section begin="server-switch"/><div class="plainlinks"> [[:m:Special:MyLanguage/Tech/Server switch|Read this message in another language]] • [https://meta.wikimedia.org/w/index.php?title=Special:Translate&group=page-Tech%2FServer+switch&language=&action=page&filter= {{int:please-translate}}] The [[foundation:|Wikimedia Foundation]] will switch the traffic between its data centers. This will make sure that Wikipedia and the other Wikimedia wikis can stay online even after a disaster. All traffic will switch on '''{{#time:j xg|2026-09-23|en}}'''. The switch will start at '''[https://zonestamp.toolforge.org/{{#time:U|2026-09-23T14:00|en}} {{#time:H:i e|2026-09-23T14:00}}]'''. Unfortunately, because of some limitations in [[mw:Special:MyLanguage/Manual:What is MediaWiki?|MediaWiki]], all editing must stop while the switch is made. We apologize for this disruption, and we are working to minimize it in the future. A banner will be displayed on all wikis 30 minutes before this operation happens. This banner will remain visible until the end of the operation. You can contribute to the [https://meta.wikimedia.org/w/index.php?title=Special%3ATranslate&group=Centralnotice-tgroup-read_only_banner&task=view&language=&filter=&action=translate translation or proofreading] of this banner text. '''You will be able to read, but not edit, all wikis for a short period of time.''' * You will not be able to edit for up to an hour on {{#time:l j xg Y|2026-09-23|en}}. * If you try to edit or save during these times, you will see an error message. We hope that no edits will be lost during these minutes, but we can't guarantee it. If you see the error message, then please wait until everything is back to normal. Then you should be able to save your edit. But, we recommend that you make a copy of your changes first, just in case. ''Other effects'': * Background jobs will be slower and some may be dropped. Red links might not be updated as quickly as normal. If you create an article that is already linked somewhere else, the link will stay red longer than usual. Some long-running scripts will have to be stopped. * We expect the code deployments to happen as any other week. However, some case-by-case code freezes could punctually happen if the operation require them afterwards. * [[mw:Special:MyLanguage/GitLab|GitLab]] will be unavailable for about 90 minutes. This project may be postponed if necessary. You can [[wikitech:Switch_Datacenter|read the schedule at wikitech.wikimedia.org]]. Any changes will be announced in the schedule. '''Please share this information with your community.'''</div><section end="server-switch"/> [[m:user:Trizek (WMF)|Trizek (WMF)]] 12:58, 15 September 2026 (UTC) <!-- Message sent by User:Trizek (WMF)@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=Distribution_list/Non-Technical_Village_Pumps_distribution_list&oldid=30513874 --> == Your feedback wanted: Remove ''(Language link added:) and similar'' edits from Special:RecentChanges == ''(Apologies for posting in English. You can help by translating it)'' Hello, I’m Danny from [[:en:w:Wikimedia_Deutschland|Wikimedia Deutschland’s]] [[m:Wikidata_For_Wikimedia_Projects|Wikidata For Wikimedia Projects]] team.<br/> We have been investigating and examining how Wikidata’s use in the [[Special:RecentChanges]] and [[Special:Watchlist]] pages can be made to be more useful, or less ‘noisy’ (fewer edits that have little value to the reader). We are currently exploring to make a change in the volume and the type of Wikidata edits that appear in these pages, and '''we need your feedback''' to help us ensure this is a positive change for the Wikis and won’t disrupt your workflows.<br/> Language links are also known as sitelinks or interlanguage links and describe when a Wikidata item is connected to a Wiki, adding it to the language dropdown tool for other connected Wikis. [[File:Types of Lang Link changes.png|x350px|frame|A variety of "Language Link" edits as seen in the Recent Changes feed]] The request for feedback is whether you support the removal of these language link edits from the Recent Changes and Watchlist feed, or would you oppose such a change and if so, why? Please share you thoughts on the dedicated '''[[m:Talk:Wikidata_For_Wikimedia_Projects/Clearer_Wikidata_Edit_Summaries/Hide_Language_Link_edits|metawiki Talk page]]'''. Further information about this change: [[m:Wikidata_For_Wikimedia_Projects/Clearer_Wikidata_Edit_Summaries/Hide_Language_Link_edits|m:Wikidata_For_Wikimedia_Projects/Hide_Language_Link_edits]] Thank you for any participation or feedback you give, -- [[m:User:Danny_Benjafield_(WMDE)|User:Danny Benjafield (WMDE)]] 12:23, 25 September 2026 (UTC) <!-- Message sent by User:Danny Benjafield (WMDE)@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=User:Danny_Benjafield_(WMDE)/MassMessage_test_list&oldid=31080985 --> == Wikidata Sitelink changes in Recent Changes and Watchlist == ''(Apologies for cross-posting in English, translating it will help spread the message)'' Editors on group 1 wikis, including Wikiquote, Wikibooks, Wikiversity, Wikivoyage, and Wikisource, will no longer see notifications on [[Special:RecentChanges|Recent Changes]] and [[Special:Watchlist|Watchlist]] when a link to ''another'' language version of a page is added, removed, or changed in its Wikidata item. This change will begin on '''October 5 at 07:00 UTC''' as a two-week trial to reduce high-volume, low-value notifications and make higher-value changes easier to identify. Editors who rely on these notifications should be aware of the change and can share feedback or concerns on the [[m:Wikidata For Wikimedia Projects/Clearer Wikidata Edit Summaries/Hide Language Link edits|project]] or [[m:Talk:Wikidata_For_Wikimedia_Projects/Clearer_Wikidata_Edit_Summaries/Hide_Language_Link_edits|talk page]].<br/>Please reach out if you have any questions, thank you! -- [[User:Danny_Benjafield_(WMDE)|Danny Benjafield (WMDE)]] ([[User_talk:Danny_Benjafield_(WMDE)|talk]]) sent via [[User:MediaWiki message delivery|MediaWiki message delivery]] ([[User talk:MediaWiki message delivery|discuss]] • [[Special:Contributions/MediaWiki message delivery|contribs]]) 12:42, 1 October 2026 (UTC) <!-- Message sent by User:Danny Benjafield (WMDE)@metawiki using the list at https://meta.wikimedia.org/w/index.php?title=User:Danny_Benjafield_(WMDE)/MassMessage_test_list&oldid=31106967 --> == Demote [[Wikiversity:CheckUser policy]]? == I am proposing that we demote that policy to a standard page, mostly for two reasons: # Considering the few amount of custodians and the size of this wiki, I'd say that this project is considered too small to have any CUs, and relying on the stewards would be a more logical choice. # We haven't elected two CUs in a few years. [[User:Codename Noreste|<span style="color: blue">Codename Noreste</span>]] /// [[User talk:Codename Noreste|⭐️✨]] 20:53, 1 October 2026 (UTC) 40d9adhrdfssegz4pit2wdzxxlttnx7 0 33462 2835365 2819055 2026-10-01T16:50:26Z ~2026-52742-61 3111957 Honestly when i searched Africa it was a joke it outlined nothing i made it comprehensive, with factual details. (SOURCES TO BE EDITED) 2835365 wikitext text/x-wiki ===== Africa is the world's second-largest and second-most populous continent, comprising 54 sovereign nations, thousands of distinct ethnic groups, and over 2,000 languages. Its landscape encompasses complex trade histories, rapid economic modernization, diverse linguistic structures, and dynamic academic and political evolution. ===== == Overview & National Symbols == === Flag of South Africa === Adopted on April 27, 1994, to mark the end of apartheid and the inauguration of Nelson Mandela, the national flag of South Africa was designed by State Herald Frederick Brownell. * '''Design Geometry:''' Features a central horizontal green band that splits into a horizontal "V" or "Y" shape extending to the hoist. * '''Color Palette:''' Incorporates six colors—red, white, green, yellow, black, and blue. * '''Symbolism:''' The "Y" pattern represents the convergence of diverse elements within South African society, taking paths toward unified forward movement. While individual colors do not carry official, singular meanings, they bridge historical flag colors used across the nation's past. == Linguistic Landscape & Regional Distribution == Africa hosts four major language phyla: Niger-Congo, Afroasiatic, Nilo-Saharan, and Khoisan. === Swahili (Kiswahili) === Swahili is a Niger-Congo language belonging to the Bantu branch. It serves as the official or national language of Tanzania, Kenya, Uganda, and the Democratic Republic of the Congo (DRC), and is widely spoken across Rwanda, Burundi, northern Mozambique, and Somalia. * '''Role:''' Operates as the primary ''lingua franca'' for East and Central Africa, uniting over 100 million speakers across trade, regional governance (East African Community), and media. === Zulu (isiZulu) === Zulu is an official language of South Africa and the native language of the Zulu people. * '''Demographics:''' Spoken as a first language by roughly 12 million people (predominantly in KwaZulu-Natal) and as a second language by millions more across Southern Africa. {| class="wikitable" |'''Language''' |'''Language Family''' |'''Primary Geographic Zone''' |'''Primary Role''' |- |'''Swahili''' |Niger-Congo (Bantu) |East Africa & Great Lakes Region |Regional Lingua Franca & Trade |- |'''Zulu''' |Niger-Congo (Bantu / Nguni) |Southern Africa (South Africa) |National Official Language |} == Economic Profile & Corporate Investment == === Multinational Investment Dynamics === Multinational enterprises increasingly prioritize direct investment across African markets due to rapid urbanization, demographic growth, and rising technology adoption. * '''Philips Strategy:''' Former Chief Market Leader Ronald de Jong noted that when aggregated, Africa's overall economic capacity rivals major developed economies such as Germany. Philips shifted focus toward local talent acquisition and regional market integration to design healthcare and lighting solutions tailored to local infrastructure conditions. * '''Venture Capital & Innovation:''' As highlighted by venture capital leaders like Philip Kiracofe, corporate venture capital (CVC) plays a pivotal role in funding tech hubs in Lagos, Nairobi, Cape Town, and Cairo. Investment flows focus on fintech, agritech, and off-grid renewable energy. == Historical Development & Trade Networks == === Ancient Kingdoms of Africa === * '''Kingdom of Aksum (100–940 CE):''' A major trading empire centered in present-day Ethiopia and Eritrea, controlling Red Sea trade routes between the Roman Empire and Ancient India. * '''Ghana, Mali, and Songhai Empires:''' West African Sahelian empires that dominated trans-Saharan trade routes in gold, salt, and manuscripts (notably in Timbuktu under Mansa Musa). * '''Great Zimbabwe (1100–1450 CE):''' A stone city empire in Southern Africa controlling gold trade networks reaching the Indian Ocean coast. === Portuguese Trade in West Africa (15th–17th Century) === Beginning with the establishment of Elmina Castle (Ghana) in 1482, Portuguese navigators established fortified trade posts along the West African coast. Initial commerce focused on gold, ivory, and Malagueta pepper, but transitioned into the early transatlantic slave trade, fundamentally shifting regional economic structures. === World War I in Africa === The First World War involved military operations across German colonies in Africa (Togoland, Kamerun, German South West Africa, and German East Africa). European powers mobilized hundreds of thousands of African soldiers and carriers, leading to major socio-economic disruption across the continent.__NOTOC__ [[Category:Continents]] [[Category:Africa]] ktyz8v22gjgk8b6c6ppdghe4d825tgx 2835479 2835365 2026-10-02T08:52:47Z PieWriter 3039865 Restored revision 2819055 by [[Special:Contributions/Atcovi|Atcovi]] ([[User talk:Atcovi|talk]]): Ai -generated (TwinkleGlobal) 2835479 wikitext text/x-wiki [[Image:Flag_of_South_Africa.svg|thumb|right|Flag of [[South Africa]]]] [[Image:Swahili_area.svg|thumb|200px|Area in [[Africa]] where [[Portal:Swahili|Swahili]] is spoken]] Africa is a continent consisting of many countries, nations and peoples. __NOTOC__ == Issues == * Philips is going to invest in Africa. According to Philips, the economy of Africa is greater than Germany's economy (source: interview with Ronald de Jong (chief market leader at Philips). Ronald says Philips will invest in Africa the coming years. They need local people who understand the market. == Schools == * [[School:African studies|School of African Studies]] == Learning projects == * [[Africa and the First World War]] * [[Student Collaboration: Africa Project]] * [[Student Collaboration: Africa Project|Peace Studies in Africa]] * [[A World of Peace, Love and Happiness#Save Africa]] == Learning resources == * [[Portuguese Trade in West Africa]] === [[Wikipedia]] === * [[w:Portal:Africa|Africa Portal]] * [[w:Africa|Africa main article]] * [[w: Ugandan general election, 2006]] === [[Wikibooks]] === * [[b:World History/Ancient Kingdoms of Africa|World History/Ancient Kingdoms of Africa]] * [[b:Volcanoes/Africa|Volcanoes/Africa]] ''-needs development-'' * [[b:Languages of Africa|Languages of Africa]] * [[b:Swahili|Swahili]] * [[b:Zulu|Zulu]] * [[b:Wikijunior:Africa|Wikijunior:Africa]] - A book about Africa and it's countries aimed at young children * ... ''[[b:Special:Search/Africa|Search for "Africa"]] at Wikibooks'' ===Learning videos=== * [https://www.youtube.com/watch?v=OpJWApJLv9U Corporate VC and Innovation in Africa | Keynote by Philip Kiracofe] [[Category:Continents]] [[Category:Africa]] a77mcqh1mchh3onmxkno1zatwb4av4j 0 38198 2835437 2807505 2026-10-02T03:31:46Z Michael Ten 654933 removed section with no content and broken link. can be added below here on page. 2835437 wikitext text/x-wiki {{Under construction}} {{history|World War II}} {{launch}} This course is about World War II, its causes and effects, and the people in it. More detailed courses will cover related topics, like the Holocaust. ==Material== * [[World War II/Causes of WWII|Causes]] * [[Medical experiments at Auschwitz]] * [[World War II/Important People|Important people]] * [[World War II/Glossary|Glossary]] * [[World War II/Timeline|Timeline]] ===See also=== * [[Looking at World War II - Text and Media|World War II in Text and Media]] * [[Did the United States need to use atomic weapons to end World War II?]] * [[Should Mein Kampf be banned?]] * [[Hitler's Germany]] ==Related books== [[World War_II/Related Books|Great WWII Authors and Books]] ==Related Wikipedia pages== * [[Wikipedia:World War II|World War II]] ==School and Department links== *[[Portal:Military History|Department of Military History]] *[[School:History|School of History]] This page was requested at [[Wikiversity:Requests]]. [[Category:World War II]] [[Category:20th-century military history]] t1ji4szhzgyph7s8mm6e32d07mm19o2 0 64248 2835445 1564241 2026-10-02T03:39:34Z Michael Ten 654933 ==Discussion questions, essay ideas, and learning related AI prompt ideas== * What is the current status of OLPC and is peripheral development development relevant at this time? If OLPC is no longer relevant, what has taken its place symbolically and archetypically (as an actual potential use case to replace its original intended purpose)? 2835445 wikitext text/x-wiki {{TOCright}} Developing OLPC Peripherals is a Fall 2008 [[Olin College Student Courses|student designed course]] at Olin College in Boston, MA. The class focuses on development of hardware peripherals for the [http://wiki.laptop.org OLPC XO] laptop. Students will work in teams to develop peripherals and meet regularly with the entire group for guest lectures and design reviews. '''Current documentation lives at [http://wiki.laptop.org/go/Inertial_navigation_peripheral the OLPC wiki]''' == Course background, description, and expectations == Developing OLPC Peripherals is a one credit student organized project class that will run in Fall 2008. Students will work in teams and pick their own projects, keeping the group updated on their progress. Guest lectures will cover topics like architecture of the laptop, circuit design, and good documentation practices. * [[/Schedule]] === Prerequisites === * Basic electronics design and fabrication * Previous experience with microcontrollers === Expectations === * Team will meet at least once a week * Project will be documented (and kept up to date) on the [http://wiki.laptop.org/go/Peripherals OLPC wiki] * Participants will attend regular status update meetings (probably once every week or every 2 weeks) * Design reviews with advising professors in attendance will be held throughout the semester (four total design reviews, every other week) ** In addition to a final design review, written reflections and documentation will be turned in at the end of the semester * Students will have access to XO laptops to test peripherals ** Each student will also become competent in XO disassembly and repair (in case of testing accidents) == Project == We have decided that we are going to build a kinetic input device that encourages collaborative physical interaction with the XO. === Phase I - User Experience === We spent the first phase of the project planning out our desired user experience and interaction with the product. Our progress at the end of this phase will resemble the end of UOCD. ==== User Interaction Diagram ==== The User Interaction Diagram shows our vision for how someone would use our product. ==== Values ==== We defined our values, the values of laptop users, and the values of parents/gov't/etc. === Phase II - System Diagramming === In this phase, we will implement all of our individual components and plan the system integration. Our progress at the end of this phase will resemble the end of POE. ==== System Diagram ==== ==== Circuit Diagram ==== === Phase III - System Integration === In this phase, we will put everything together and make it work. Our progress at the end of this phase will resemble the end of SCOPE. === Phase IV - Documentation === In this phase, we will clean up all of our documentation and make sure the project is reproducible by other parties. Our progress at the end of this phase will resemble something not done at Olin. == How to join == Contact [[User:Nlee|Nikki Lee]]. === Participants === * [[User:Nlee|Nikki Lee]] (Olin College) * [[User:Greg marra|Greg Marra]] (Olin College) * [[User:Andreatl|Andrea Lai]] (Olin College) * [[User:jgorasia|Jay]] (Olin College) * [[User:Kelcy|Kelcy Adamec]] (Olin College) * Carl Tappan * ???: Ian Daniher (Senior @ Cincinnati Hills Christian Academy - Olin Hopeful) === Mentors === * Oscar Mur-Miranda * Lynn Stein * Brad Minch == Meeting notes == * [[User talk:Andreatl/8282008|8282008]] - August 28, planning ==Discussion questions, essay ideas, and learning related AI prompt ideas== * What is the current status of OLPC and is peripheral development development relevant at this time? If OLPC is no longer relevant, what has taken its place symbolically and archetypically (as an actual potential use case to replace its original intended purpose)? [[Category:Olin College]] [[Category:One Laptop Per Teacher]] [[Category:Corporate social responsibility|{{SUBPAGENAME}}]] i20w5pa91r86ur6faiv13if4rral24m 2835447 2835445 2026-10-02T03:42:20Z Michael Ten 654933 /* Discussion questions, essay ideas, and learning related AI prompt ideas */ edited and added 2835447 wikitext text/x-wiki {{TOCright}} Developing OLPC Peripherals is a Fall 2008 [[Olin College Student Courses|student designed course]] at Olin College in Boston, MA. The class focuses on development of hardware peripherals for the [http://wiki.laptop.org OLPC XO] laptop. Students will work in teams to develop peripherals and meet regularly with the entire group for guest lectures and design reviews. '''Current documentation lives at [http://wiki.laptop.org/go/Inertial_navigation_peripheral the OLPC wiki]''' == Course background, description, and expectations == Developing OLPC Peripherals is a one credit student organized project class that will run in Fall 2008. Students will work in teams and pick their own projects, keeping the group updated on their progress. Guest lectures will cover topics like architecture of the laptop, circuit design, and good documentation practices. * [[/Schedule]] === Prerequisites === * Basic electronics design and fabrication * Previous experience with microcontrollers === Expectations === * Team will meet at least once a week * Project will be documented (and kept up to date) on the [http://wiki.laptop.org/go/Peripherals OLPC wiki] * Participants will attend regular status update meetings (probably once every week or every 2 weeks) * Design reviews with advising professors in attendance will be held throughout the semester (four total design reviews, every other week) ** In addition to a final design review, written reflections and documentation will be turned in at the end of the semester * Students will have access to XO laptops to test peripherals ** Each student will also become competent in XO disassembly and repair (in case of testing accidents) == Project == We have decided that we are going to build a kinetic input device that encourages collaborative physical interaction with the XO. === Phase I - User Experience === We spent the first phase of the project planning out our desired user experience and interaction with the product. Our progress at the end of this phase will resemble the end of UOCD. ==== User Interaction Diagram ==== The User Interaction Diagram shows our vision for how someone would use our product. ==== Values ==== We defined our values, the values of laptop users, and the values of parents/gov't/etc. === Phase II - System Diagramming === In this phase, we will implement all of our individual components and plan the system integration. Our progress at the end of this phase will resemble the end of POE. ==== System Diagram ==== ==== Circuit Diagram ==== === Phase III - System Integration === In this phase, we will put everything together and make it work. Our progress at the end of this phase will resemble the end of SCOPE. === Phase IV - Documentation === In this phase, we will clean up all of our documentation and make sure the project is reproducible by other parties. Our progress at the end of this phase will resemble something not done at Olin. == How to join == Contact [[User:Nlee|Nikki Lee]]. === Participants === * [[User:Nlee|Nikki Lee]] (Olin College) * [[User:Greg marra|Greg Marra]] (Olin College) * [[User:Andreatl|Andrea Lai]] (Olin College) * [[User:jgorasia|Jay]] (Olin College) * [[User:Kelcy|Kelcy Adamec]] (Olin College) * Carl Tappan * ???: Ian Daniher (Senior @ Cincinnati Hills Christian Academy - Olin Hopeful) === Mentors === * Oscar Mur-Miranda * Lynn Stein * Brad Minch == Meeting notes == * [[User talk:Andreatl/8282008|8282008]] - August 28, planning ==Discussion questions, essay ideas, and learning related AI prompt ideas== * What is the current status of OLPC and is peripheral development development relevant at this time? If OLPC is no longer relevant, what has taken its place symbolically and archetypically (as an actual potential use case to replace its original intended purpose)? ===An answer to above question=== ==== Current status of OLPC ==== {{Template:AI-generated-section}} * '''Hardware:''' Defunct. Custom XO laptop production ceased around 2014–2015; community wikis are read-only historical archives. * '''Deployments:''' Early national adopters like Uruguay's ''Plan Ceibal'' transitioned completely to standard commercial laptops, tablets and maker electronics. * '''Organization:''' Shifted away from hardware toward software distributions, learning materials, and advisory roles. == Peripheral development relevance == * '''Educational / practical deployments:''' Irrelevant due to obsolete processors, unsupported display hardware, and abandoned operating systems. * '''Niche use:''' Only relevant for retro-computing preservation, museum maintenance, or legacy Linux hobby projects. == Symbolic and archetypal successors == * '''Pedagogical & constructionist tool:''' '''Raspberry Pi and BBC micro:bit''' inherited the low-cost, open, hackable ethos aimed at teaching programming and physical computing rather than passive consumption. * '''Offline & grid-Independent knowledge:''' '''Internet-in-a-Box (IIAB) and Kiwix''' fulfill the promise of delivering open educational resources (Wikipedia, Khan Academy, maps) over local Wi-Fi without internet or power-grid reliance. * '''Hardware freedom & repairability:''' '''Framework Laptop and MNT Reform''' represent the XO's open-hardware, user-serviceable, anti-obsolescence design philosophy. * '''Institutional mass deployment:''' '''Chromebooks and cheap Android tablets''' captured the logistical reality of "one device per child," though they inverted the model into centralized, cloud-dependent, managed consumption terminals. [[Category:Olin College]] [[Category:One Laptop Per Teacher]] [[Category:Corporate social responsibility|{{SUBPAGENAME}}]] 894ak8plf7benrp7x9k7gipfpurr66a 0 70160 2835466 2833870 2026-10-02T07:43:50Z Hamdanibrahi 3111248 /* Writing for a blog */ 2835466 wikitext text/x-wiki <div style="margin-left: auto; margin-right: auto; width:100%"> <div style="background-color:#f7f8ff;{{text color default}}; text-align:justify; padding:5px; border:1px solid #8888aa; border-right-width:2px; border-bottom-width:2px; margin-bottom:2em" > [[Image:Crystal_Clear_app_kaddressbook.png|left|50px|Placeholder]] <div style="font-weight:bold; font-size:125%">Blogs and blogging for Web 2.0 professional use</div> ---- A [[w:Blog|blog]] is a type of website that can be used for a variety of reasons. Blogs can be used to describe events, showcase graphical design, and convey perceptions of the world. They can be maintained by an individual or multiple writers, and tend to have a particular subject matter that they discuss. Entries are typically displayed in reverse-chronological order. Nearly any type of blog can be used professionally. Some provide commentary on news, or function as a personal diary. No matter what type of blog you are writing, it is capable of furthering your professional career. A blogger may be paid to generate traffic in order to give advertisements more exposure. The relationship between a blogger and a company may also be direct, as in some cases popular bloggers are paid to promote a company's product. Many people, such as artists and writers, also use blogs to promote their own services and products. </div> </div> __TOC__ == The Complete Guide to Portable Card Machines for Small Businesses == Customers expect to pay however they like, and more often than not that means a card or a phone. [https://speedypayments.co.uk/portable-card-machines/ Portable card machines] let you take payments anywhere, from a market stall to a customer's doorstep. This guide explains what portable card machines are, how they work, the benefits, and how to choose the right one for your business. === What Are Portable Card Machines? === Portable card machines are compact, wireless payment terminals that accept debit cards, credit cards, contactless taps, and mobile wallets such as Apple Pay and Google Pay. Unlike traditional countertop terminals, they run on Wi-Fi, mobile data (4G or 5G), or Bluetooth, so you aren't tied to a fixed phone line or checkout desk. Most models are lightweight and fit in a pocket or bag. They typically include a built-in screen, a keypad, a card reader, and a rechargeable battery. Many can also print receipts or send them by email or text. === How Do Portable Card Machines Work? === When a customer pays, the machine reads their card through chip and PIN, contactless tap, or magnetic stripe. The payment details are encrypted and sent to your payment provider, which checks the funds and approves or declines the transaction within seconds. Approved payments are then settled into your business bank account, usually within one to two working days, depending on your provider. Some portable card machines are standalone devices with their own SIM or Wi-Fi connection. Others are smaller card readers that pair with a smartphone or tablet through an app. === Key Benefits of Portable Card Machines === ==== Take Payments Anywhere ==== The biggest advantage is mobility. Whether you run a food truck, a mobile salon, a delivery service, or a pop-up shop, you can take payment on the spot. Restaurants also use them for pay-at-table service, which speeds up the experience and keeps cards in the customer's sight. ==== Faster Checkouts and Shorter Queues ==== Contactless payments take just seconds. With a portable machine, staff can serve customers anywhere on the shop floor, reducing queues during busy periods and improving the overall customer experience. ==== Increased Sales ==== Many customers carry little or no cash. Accepting cards means you never lose a sale because someone can't pay. Cardholders also tend to spend more per transaction than cash users. ==== Improved Security ==== Modern portable card machines meet strict security standards, including PCI DSS compliance and end-to-end encryption. Handling less cash also lowers the risk of theft, counting errors, and trips to the bank. ==== Better Record-Keeping ==== Most providers offer online dashboards or apps that track every sale, so you can view daily takings, download reports, and simplify bookkeeping and tax preparation. Many integrate with accounting software such as Xero or QuickBooks. === Types of Portable Card Machines === ==== Standalone Wireless Terminals ==== These all-in-one devices connect via Wi-Fi or a built-in SIM and operate independently of any phone. They suit businesses that need dependable performance, long battery life, and built-in receipt printing. ==== Smartphone Card Readers ==== These small readers connect to your phone or tablet through Bluetooth and use a free app to process sales. They are the cheapest way to start and are ideal for sole traders, market sellers, and tradespeople. ==== Smart POS Terminals ==== These portable machines run on Android-style software and offer extra features such as itemised menus, inventory tracking, staff logins, and online ordering links. They work well for busy restaurants, cafés, and retailers who want more than basic payments. === How to Choose the Right Portable Card Machine === ==== Consider Connectivity ==== Think about where you'll work. If you often trade in areas with weak mobile signal, choose a machine that can switch between Wi-Fi and mobile data, or one that stores transactions offline and processes them when the connection returns. ==== Check Battery Life ==== A good portable card machine should last a full working day on a single charge. Look for models with fast charging and, ideally, a charging dock for convenience. ==== Compare Fees and Contracts ==== Costs vary significantly between providers. Look closely at: * '''Transaction fees:''' a percentage of each sale, often between 1% and 2.5% * '''Monthly fees:''' some providers charge for the terminal or service * '''Hardware costs:''' upfront purchase price or rental * '''Contract length:''' some providers lock you in for 12 to 24 months * '''Settlement times:''' how quickly money reaches your account Pay-as-you-go plans suit seasonal or low-volume businesses, while higher-volume traders may save money with a monthly plan and lower rates. ==== Look at Payment Options ==== Make sure the machine accepts all the payment types your customers use, including chip and PIN, contactless, Apple Pay, Google Pay, and major card brands such as Visa, Mastercard, and American Express. ==== Think About Receipts and Reporting ==== Decide whether you need printed receipts or whether digital ones will do. Also check what reporting tools come with the device, as good dashboards can save hours of admin. ==== Prioritise Customer Support ==== When a payment fails during a busy Saturday market, you need quick help. Choose a provider with responsive UK-based support and clear troubleshooting resources. === Who Uses Portable Card Machines? === Portable card machines are popular across many industries: * '''Market traders and street food vendors''' * '''Mobile hairdressers, beauticians, and personal trainers''' * '''Taxi and delivery drivers''' * '''Tradespeople such as plumbers, electricians, and gardeners''' * '''Restaurants, cafés, and bars using pay-at-table service''' * '''Event organisers and pop-up retailers''' === Tips for Getting the Most From Your Portable Card Machine === # '''Keep it charged.''' Charge the device overnight and carry a power bank for long days. # '''Update the software.''' Updates improve security and performance. # '''Test the signal.''' Check connectivity before you arrive at a new location. # '''Protect the device.''' A sturdy case guards against drops and spills. # '''Review your statements.''' Check fees and settlements regularly to spot errors. # '''Train your staff.''' Make sure everyone knows how to process payments, refunds, and receipts. === Are Portable Card Machines Worth It? === For most businesses, the answer is yes. The cost of a portable card machine is usually quickly offset by increased sales, faster service, and reduced cash handling. With affordable options available, even the smallest business can look professional and accept payments confidently. === Final Thoughts === Portable card machines have made it easier than ever to accept payments wherever your business takes you. By choosing a device with reliable connectivity, transparent fees, strong security, and good support, you can give customers the convenient payment experience they expect. Compare providers carefully, think about how and where you trade, and pick a machine that can grow with your business.{{Reflist}} [[Category:Web 2.0 for Professional Use]] 9xw9lg94d3aalnn3zp18gdhz5bw6wxx 2835471 2835466 2026-10-02T08:20:19Z NguoiDungKhongDinhDanh 2922842 Reverted edit by [[Special:Contributions/Hamdanibrahi|Hamdanibrahi]] ([[User_talk:Hamdanibrahi|talk]]) to last version by [[User:MathXplore|MathXplore]] using [[Wikiversity:Rollback|rollback]] 2773707 wikitext text/x-wiki <div style="margin-left: auto; margin-right: auto; width:100%"> <div style="background-color:#f7f8ff;{{text color default}}; text-align:justify; padding:5px; border:1px solid #8888aa; border-right-width:2px; border-bottom-width:2px; margin-bottom:2em" > [[Image:Crystal_Clear_app_kaddressbook.png|left|50px|Placeholder]] <div style="font-weight:bold; font-size:125%">Blogs and blogging for Web 2.0 professional use</div> ---- A [[w:Blog|blog]] is a type of website that can be used for a variety of reasons. Blogs can be used to describe events, showcase graphical design, and convey perceptions of the world. They can be maintained by an individual or multiple writers, and tend to have a particular subject matter that they discuss. Entries are typically displayed in reverse-chronological order. Nearly any type of blog can be used professionally. Some provide commentary on news, or function as a personal diary. No matter what type of blog you are writing, it is capable of furthering your professional career. A blogger may be paid to generate traffic in order to give advertisements more exposure. The relationship between a blogger and a company may also be direct, as in some cases popular bloggers are paid to promote a company's product. Many people, such as artists and writers, also use blogs to promote their own services and products. </div> </div> __TOC__ == Writing for a blog == ==== Writing A Good Blog ==== Starting off, you should always make sure that you use proper grammar and spell words correctly. There are always exceptions to the rules, though, and technically one could write a blog with intentional bad grammar to represent culture or parody. However, as a general rule, such styles are considered unprofessional. Another important rule is that you should adhere to an ethical code of conduct. This means that you should not report information that you know is false, and you should avoid slander. Gossip and satirical blogs may take a liberal view of this rule, but generally speaking, these rules are good to follow. If people find you to be a credible source of information, you will be more successful in the long run. Make your content interesting and make what you are writing about clear. The title of your blog and the title of your blog posts should always give a clear indication of what you will be writing about. If you yourself do not find the content that you are writing about to be interesting, then chances are that your readers will not, either. Try to avoid update posts just for the sake of updating, and write something that says something interesting about the world. ==== Promoting Your Blog ==== Creating a blog is easy, but making it successful takes work and practice. There are many different ways to gather an audience and keep it. ===== Gathering An Audience ===== One of the best ways to gather an audience is to simply let people know that you're out there. Tell your friends, post on forums that are relevant to your topic, and use keywords and tags to make it easier to find. People are always looking to read a good article, but they have to be able to find it. Having an easy to remember blog name helps, as people can pass on your blog by word of mouth. Forums are an even better way of showing people what you are up to, because they often have a greater number of visitors than any personal site does. Finally, try linking to other people's blogs and making friends with other bloggers. Linking to another blogger will often get you linked back. ===== Keeping Your Audience ===== Provided you already have an audience, it is important to update at regular intervals. If you plan on not updating very often, let your readers know when you do plan to update, otherwise they may simply lose interest. You also need to realize that your audience will have certain expectations of you. If your blog has a title or entries that focus on a particular subject, changing venues will throw off readers. Having a blog that covers a variety of subjects is good, but you need to let your readers know what it covers. If you write sponsored blogs, it's important to remember that doing so incorrectly may alienate your readers. First and foremost, if you are paid to write a sponsored blog, you must write an honest review. It's also important to let your audience know that you are being sponsored, as this lends to your credibility. Doing otherwise is dishonest, and may damage your reputation with both the sponsor and the reader. Do not make the majority of your content sponsored. People come to read your blog for your opinions, but if you only write biased articles for sponsors, this will damage your credibility in the long run. People may no longer see your blog as yours, but rather as a corporate tool. Finally, always try to keep up your end up of the bargain. If you are being paid to write a certain type of article, you should be sure to write what you agreed to. <ref name="5 Tips for Pay-Per-Post Success"> [http://onlinebusiness.about.com/od/monetization/tp/pay-per-post-success.htm 5 Tips for Pay-Per-Post Success]</ref> ==== Collaborative Blogging ==== While individual blogs can certainly be correspondingly written by a single individual, the avenue of collaborative blogging often provides the opportunity for a much more active, dynamic blogging experience. Obviously with more authors contributing to a particular blog, it is more likely that the blog can be more frequently contributed to. The burden or load of carrying an individual blog by oneself is certainly made easier by sharing the load with fellow contributors in a collaborative blog. Also with more authors contributing to a particular blog, the greater the possibility for an even more intriguing variety of voices and personalities. The interaction of these different voices with one another can certainly add a refreshing dynamic unachievable in the realm of individual blogging. An interesting variety of blogging voices within a single blog increases the potential for a wider variety in readership across the world. Though employing many voices in one setting can be fairly attractive for attaining a wide readership, readers may be pushed away if the blog is not well run and well organized by an administrator or group of administrators. Collaborative blogging may consist of a small or large group of people who personally know each other, or it may consist of a small or large group of people who do not. An example of the latter of these collaborative blogs is the politically liberal blog [http://www.dailykos.com DailyKos], which allows blogging access to essentially anybody who desires it. Because of the rising popularity of and interest in communal blogs, many blog platforms in addition to individual blogs now offer some kind of collaborative blogging feature. [http://www.blogger.com Blogger] and [http://wordpress.com WordPress] are only two of many blogging platforms which allow access for multiple contributing authors, editors, and administrators. == Choosing a blog host == ==== [[/Blog Hosts/]] ==== The first step in the creation process of a blog is choosing a blog host. Alternately, you can decide to host your own blog. A variety of competing blog hosts offer unique features that make them the best choice for different bloggers. Storage space, bandwidth, [[w:Wysiwyg|WYSIWYG]] interfaces, themes and pricing are all options to consider when picking out a blogging host. == Hosting your own blog == ==== [[/Web hosting/]] ==== With literally hundreds of sites offering domain registration and web hosting, it can be difficult to find the best service to suit your needs. Many web hosts offer tons of storage space and bandwidth, but have unreliable tech support or other problems that are only encountered after committing to a monthly plan. While it’s possible to buy a hosting plan that comes with a free domain name, it’s recommended that registering a domain and buying web hosting should be done separately to ensure that the web host does not retain control of the domain name. The site [http://webhostingtalk.com Webhostingtalk] is a hub of users sharing their experiences on the best and the worst web hosting available on the internet. ==== Using Dreamweaver ==== Adobe's Dreamweaver is a XHTML generator<ref>Hands-on Training's Adobe Dreamweaver CS3 by Garrick Chow</ref>, giving users the option to either code a Web site visually or through HTML coding. The visual component is what makes Dreamweaver an indispensable tool for stunning Web site design. Those with little to no experience with coding may find Dreamweaver daunting and confusing at first. The program is built to cater towards intermediate to advanced Web site designers, though a technologically savvy person may be able to trial-and-error their way through. For the unassuming professional, an excellent guide is Garrick Chow's Hands-on Training's Adobe Dreamweaver CS3, which includes a CD-ROM with exercise files and videos. As part of Adobe's Creative Suite, Dreamweaver CS3 is the best option seeing as it is more compatible with the other Adobe programs such as Photoshop and Flash. Adobe also offers [http://www.adobe.com/support/dreamweaver/tutorial_index.html extensive tutorials] to help new users learn how to use Dreamweaver. ==== [[w:Blog_software#Free_and_open_source_software|Blogging software]] ==== To host a blog on your own website, you'll want to choose from one of many available blogging software options. Some popular choices are listed below. *[http://wordpress.org/ WordPress] *[http://movabletype.org/ MovableType] *[http://drupal.org/ Drupal] == Reference == {{Reflist}} [[Category:Web 2.0 for Professional Use]] 486tn3rgr96ptw2xgch203s0yufd6l1 0 89393 2835366 2018482 2026-10-01T16:54:03Z ~2026-52975-77 3111959 /* Radioactive Decay */ Fixed a typo where instead of saying "Uranium-234" it said "Uranium-243." 2835366 wikitext text/x-wiki This is an introduction to nuclear chemistry, the chemistry of different nuclear reactions and radioactive materials. ==<big>The Atom</big>== As you probably know, the atom is made of electrons, neutrons and protons. The nucleons are made of subatomic particles. Atoms were first theorized by the Greeks in 350 B.C. They thought that everything had its own type of atoms e.g. humans have human atoms and dogs have dog atoms. This model existed until the 1800's. Then, John Dalton, an English chemist said that atoms can combine in specific ratios to create compounds. Then in 1897 Joseph John Thompson discovered the electron and said that there was an equal distribution of positive and negative charges within the atom. In 1911, Ernest Rutherford performed his gold foil experiments, and discovered that the atom had a positively charged center, and had electrons moving around it. In 1913, Neil Bohr created the planetary model where the electrons would orbit the positively charged center of the atom like the planets orbit the Sun. [[Image:Helium atom QM.svg|right|thumb|An illustration of the helium atom, depicting the nucleus (pink) and the electron cloud distribution (black). The nucleus (upper right) in helium-4 is in reality spherically symmetric and closely resembles the electron cloud, although for more complicated nuclei this is not always the case. The black bar is one ångström, equal to 10−10 m or 100,000 fm. This is an image of the modern atomic model, called the Charged Cloud Model. ]] The modern atomic theory is that the electrons do not follow a specific path around the nucleus and that you can never know the exact location of an electron in an atom, but only have a probability of finding them.<ref>"Lesson 3-2 Development of the Atomic Model." Fordham Preparatory School - Home. 2004. Web. 5 Dec 2009. <http://www.fordhamprep.org/gcurran/sho/sho/lessons/lesson32.htm>. </ref> ==<big>Isotopes</big>== Isotopes are when the number of neutrons and protons in an atom are different. Also, having a large difference between the number of protons and neutrons can cause an elements isotope to become radioactive, even if the original element wasn't (e.g. in the case of Carbon-14). Radioactive substances produce radiation in the form of particles (such as alpha particles and beta particles) and electromagnetic waves (e.g. Gamma rays).<ref>"Isotopes." Web. 5 Dec 2009. <http://www.colorado.edu/physics/2000/isotopes/index.html>. </ref> The number of neutrons and protons added together in an isotope determine its mass number. ==<big>Radiation</big>== I am doing this part of nuclear chemistry early in the article since there is a lot of confusion about what radiation is. It is simply the process of emitting energy in the form of particles or waves. It can be dangerous, but most types are not. There are two types of radiation, ionizing and non-ionizing. Ionizing radiation has the power to remove electrons from atoms, creating ions (we will learn about that later). That is why they are so dangerous, and can cause cancer (but they can be used in good ways: to kill cancer cells, generate power, sterilize substances etc.). The four main types being alpha, beta, x-ray and gamma. An alpha particle is a nucleus of helium with a mass number of 4. <ref>http://hyperphysics.phy-astr.gsu.edu/hbase/nuclear/radact.html</ref> That means that there are two neutrons and two protons in the particle. A beta particle is simply an electron, and gamma and X-rays are pure energy, with no mass or charge. X-rays are used to diagnose medical problems, such as a broken arm or leg. Even though they have the ability to mutate cells and DNA as well as cause cancer. <ref>http://www.epa.gov/rpdweb00/understand/health_effects.html</ref> They are extremely useful in the medical field. Gamma rays are often used to kill cancer cells. Because cancer cells grow so fast, gamma rays are much more effective at killing them than normal, healthy cells. Non-ionizing radiation does not have the ability to change atoms into ions, thus not being able to cause cancer.<ref>"Non-Ionizing Radiation Information | Radiation Safety | Safety Programs | EHRS." Penn: University of Pennsylvania. October 27, 2009. University of Pennsylvania, Web. 5 Dec 2009. <http://www.ehrs.upenn.edu/programs/radiation/nonionizing_faq.html>. </ref> Here is a diagram of the electromagnetic spectrum: [[Image:OSHA_radiation_spectrum.jpg‎|center|This is the electromagnetic spectrum. ]] ==<big>Ions</big>== What are Ions? Well they are simply atoms or molecules that have a charge, where they have less or more electrons than they should. <ref>"WordNet Search - 3.0." Princeton University, Web. 5 Dec 2009. <http://wordnetweb.princeton.edu/perl/webwn?s=ion>. </ref> There are two types of ions, anions and cations. Anions have more electrons than protons, giving them a negative charge <ref>http://dictionary.reference.com/browse/anion</ref> and cations have more protons than electrons, giving them a positive charge.<ref>http://dictionary.reference.com/browse/cation</ref> If an ion has unpaired electrons in them, they become very reactive. <ref>http://en.wikipedia.org/wiki/Radical_ion</ref> An example of an ion is sodium, which reacts violently with water. When combined with chlorine it creates table salt. In fact it is so reactive that it has to be stored in a hydrocarbon (e.g. gasoline, kerosene etc.) otherwise it will explode. <ref>http://en.wikipedia.org/wiki/Sodium</ref>.[[Image:Sodium.jpg|center|thumb|This is sodium, being stored in mineral oil.]] ==<big>Radioactive Decay</big>== Sometimes elements are unstable, and they decay into more stable elements. Some do this slowly, in a matter of thousand, millions or even billions of years, while others do it quickly, sometimes in a matter of milliseconds. Any radioactive isotope has a half life, that is how long it will take half of a certain amount of radioactive material to decay into a different isotope. For instance, Uranium-234 has a half life of 245,000 years,<ref>http://www.ieer.org/fctsheet/uranium.html</ref> so after 245,000 years a 1-gram sample of Uranium-234 would have only 1/2 gram of Uranium-234 in it. For this isotope, every 245,000 the amount of Uranium-234 in a sample is cut in half. So after 490,000 years, 1/4 of a grams of Uranium-234 will remain in the sample. Different isotopes of different elements generally have different half-lifes. For instance, Polonium-214 has a half life of 163 microseconds (a microsecond is one-millionth of a second). <ref>http://www.ieer.org/fctsheet/uranium.html</ref> When this process is started artificially, it is called transmutation. <ref>http://faculty.ncc.edu/LinkClick.aspx?fileticket=Fkhb0%2FAcPfE%3D&tabid=1920</ref> This is an example of an artificial transmutation, this one being called a fission reaction: [[File:Fission_(PSF).png‎|center|thumb|This is a fission reaction ]] == <big>References</big> == <references/> [[Category:Nuclear chemistry]] 5zegjwqfuoqpfgbacw7kmpbayqgp4zu 0 96387 2835395 2835259 2026-10-01T22:28:30Z Jtneill 10242 /* Length (word count) */ 2835395 wikitext text/x-wiki {{title|Book chapter — Guidelines}} <div style="text-align: center;">''Collaborative online book chapter authoring'' <!-- ---------------------------------- ---> <!-- Count down --> <!-- ---------------------------------- ---><!-- {{countdown |year = 2026 |month = 10 |day = 12 |hour = 0 |event = this assessment is due }} --><!-- {{Motivation and emotion/Assessment/In development}} --> {{/Contents/}}</div> {{TOCright}} ==Overview== * Weight: 50% * Due {{/Due}} * Tasks ** Author an online [[Motivation and emotion/Book|book chapter]] (up to 4,000 words) that explains key psychological theory and research about a unique, specific motivation or emotion topic. ** Develop the chapter by building on the [[Motivation and emotion/Assessment/Topic|topic development]] plan and addressing feedback. ** Contribute to the development of other book chapters (social contribution). * Follow the [[#Instructions|instructions]] and address the [[#Marking criteria|marking criteria]]. ==Purpose== The purpose of the book chapter is to explain and critically evaluate what psychological science says about a specific motivation or emotion topic, and to demonstrate how this knowledge can be applied to understanding and improving human behaviour in everyday life. ==Marking and feedback== * Submissions will be marked according to the [[#Marking criteria|marking criteria]] and [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing marking rubric]. * Marks will be provided via {{Motivation and emotion/Canvas}} when the university releases unit results (see [https://www.canberra.edu.au/about-uc/key-dates/ Key dates]). * Up to 5 bonus marks will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level (see [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60 rubric]). * Written feedback about how well the chapter addresses the marking criteria will be available via the topic's Wikiversity discussion page. * Follow up with the [[Motivation and emotion/About/Staff|unit convener]] if you have any questions. ==Extensions and late submissions== * Apply for extension using the unit's online Extension Application Form (see {{Motivation and emotion/Canvas}}) with appropriate documentary evidence. * Submissions will be accepted up to 3 days late (-10% per day). * If you don't submit this assessment it is unlikely that you will pass the unit. ==Learning outcomes== How the unit's [[Motivation and emotion/About/Learning outcomes|learning outcomes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto; vertical-align:top;" |- | style="width:40%;" | '''Learning outcome''' | style="width:60%;" | '''Assessment task''' |- | style="vertical-align:top;" | Integrate theories and current research towards explaining the role of motivation and emotions in human behaviour. | style="vertical-align:top;" | Use the most relevant theories and peer-reviewed research to explain a specific motivation or emotion topic. |- | style="vertical-align:top;" | Critically apply knowledge of motivation or emotion to an indepth understanding of a specific topic in this field. | style="vertical-align:top;" | Explain how psychological science can be applied to a specific motivation or emotion topic. Use figures, examples, and/or other interactive learning features to illustrate how this knowledge can apply to understanding human behaviour in everyday life. |} ==Graduate attributes== How the unit's [[Motivation and emotion/About/Graduate attributes|graduate attributes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto;" |- ! style="width:20%;" | Category ! style="width:20%;" | Graduate attribute ! style="width:60%;" | Assessment task |- | rowspan="4" style="vertical-align:top;" | '''Be professional''' | style="vertical-align:top;" | Communicate effectively | style="vertical-align:top;" | Review scholarly knowledge in an open, online environment and address feedback. |- | style="vertical-align:top;" | Display initiative and drive | style="vertical-align:top;" | Produce an online book chapter about a novel motivation or emotion topic. |- | style="vertical-align:top;" | Up-to-date knowledge and skills | style="vertical-align:top;" | Utilise the most relevant psychological theory and research to address a practical question. |- | style="vertical-align:top;" | Solve problems via thinking | style="vertical-align:top;" | Use critical thinking to explain how psychological science can address real-world problems. |- | rowspan="3" style="vertical-align:top;" | '''Be a global citizen''' | style="vertical-align:top;" | Informed and balanced | style="vertical-align:top;" | Provide a balanced, critical chapter which is accessible to a lay audience. |- | style="vertical-align:top;" | Communicate diversely | style="vertical-align:top;" | Collaborate with peers to communicate knowledge openly with a global audience. |- | style="vertical-align:top;" | Creative use of technology | style="vertical-align:top;" | Learn how to collaborate using wiki technology. |- | rowspan="2" style="vertical-align:top;" | '''Be a lifelong learner''' | style="vertical-align:top;" | Engage in new ideas | style="vertical-align:top;" | Engage in a collaborative learning culture by incorporating feedback and suggestions. |- | style="vertical-align:top;" | Evaluate and adopt new technology | style="vertical-align:top;" | Experience project work in a collaborative, online editing environment. |} ==Instructions== The book chapter should communicate your understanding of the topic based on the best available psychological theory and research. Explain and apply the most relevant evidence in a clear, engaging, and accessible way. The aim is to demonstrate your ability to synthesise and critically evaluate psychological science in order to understand and respond to a specific motivation or emotion phenomenon. The following instructions should be used to guide the development of the book chapter. ===Theme=== * Chapters should fit the book theme which is "understanding and improving our motivational and emotional lives using psychological science" ===Audience=== * The target audience is a general (non-topic-expert) reader interested in personal growth and development based on knowledge in psychological science (theory and research). This is a [[w:science communication|science communication]] exercise. ===Wikiversity=== * Present the chapter as a single page on the [[Main Page|English Wikiversity]] website. A link to the chapter should appear in the [[Motivation and emotion/Book|table of contents]] along with the lead author's Wikiversity user name ===Topic=== * The title and sub-title must be approved by the [[Motivation and emotion/About/Staff|unit convener]] ===Collaboration and feedback=== * Chapters should be independently developed and written primarily by the lead author, but collaboration is strongly encouraged (e.g., by incorporating useful edits and feedback from others) * [[Motivation and emotion/Assessment/Using generative AI|Generative AI]] may be used with appropriate acknowledgement * Lead authors are encouraged to seek feedback about the chapter during the drafting process (e.g., start a {{Motivation and emotion/Canvas}} discussion thread<!-- (use the chapter title and subtitle in the subject line and include a clickable hyperlink to the chapter in the message)-->) * Feedback is usually best placed on the chapter's wiki discussion page * Feedback on the [[Motivation and emotion/Assessment/Topic|topic development]] (chapter plan) will be provided by the [[Motivation and emotion/About/Staff|unit convener]] ===Length (word count)=== {{Anchor|Wordcount}}{{Anchor|Word count}} * There is no minimum length * Maximum 4,000 words ** There is no additional 10% allowance ** Words beyond the maximum will not be considered for marking purposes ** Count everything from top to bottom of the editable page (in view mode, not edit mode) including the title, subtitle, headings, text, citations, tables, figures, references, see also, and external links ** Don't count menu text across the top and down the left, or categories at the bottom ** How to count: *** Google Chrome extension: [https://chromewebstore.google.com/detail/word-counter/cbjddaobmdfhbfgdgjocbhklpmclcboe Word Counter]. This extension is probably the easiest reliable method for counting words on a Wikiversity page. However, UC recently started blocking this extension on UC devices. *** Website: Paste the URL into [https://hsuper.tools/web-page-word-counter Webpage Word Counter] (it overcounts by ~100 words because it includes menus etc.) *** Word processor: Cut and paste into a word processor (i.e., copy starting at title and finishing with the last external link) * If the chapter exceeds the maximum word count, see [[/Word count|these suggestions]] for strategies to reduce the length while retaining the key content. ===Submission=== * Submit the chapter URL (website address), your Wikiversity user name, and a PDF of the chapter via {{Motivation and emotion/Canvas}} ==Marking criteria== [[File:Balanced scales.svg|right|125px]] Book chapters will be marked against the following criteria. ===Overview (5%)=== * Scenario: Provide an engaging scenario or case study in a feature box, with an illustrative figure * Problem statement: Easy to read and understand outline of the key concepts and explanation of practical/real-world problem to be solved * Focus questions: Establish [[/Focus questions|focus questions]] which align with the sub-title and subsequent heading structure ===Theory (20%)=== * Clearly explain the theoretical framework for understanding the topic * Select the most relevant psychological theories/models that apply to the problem. Depending on the topic, this may involve focusing on a single theory or comparing and contrasting two or more theories. * Use at least the best dozen or so peer-reviewed theory references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Clearly explain and apply the theory(ies) * Include illustrative examples, such as case studies * Demonstrate a critical perspective ===Research (25%)=== * Clearly explain how key, peer-reviewed research findings apply to the problem * Use at least the best dozen or so peer-reviewed research references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Include relevant major reviews (such as systematic reviews and meta-analyses) * [[w:Critical thinking|Critical analyse]] the key research findings, including limitations and implications ===Integration (10%)=== * Integrate discussion of theory and review of relevant research * Use research to critically inform interpretation and application of the theory(ies) ===Conclusion (5%)=== * Clear and concise communication of key points and take-home messages * Aligned with the subtitle and focus questions, with implications for the [[Motivation and emotion/Book/Theme|book theme]] ===Style (20%)=== * Overall ** Present and illustrate the problem and knowledge in an interesting way, using a logical structure, clear layout, correct spelling and grammar, and [[APA style]] ** [[/Readability|Readable]] for a layperson interested in psychological science ** Address the [[#Theme|book theme]] by providing practical, academically sound, self-improvement information ** Address an international audience (i.e., avoid an overly local or national perspective) ** Use default wiki style for paragraph alignment, font colour, type, and size, and heading styles ** Use Australian spelling (e.g., hypothesise, behaviour, fulfilment) rather than American spelling (e.g., hypothesize, behavior, fulfillment) ** Correct grammar (e.g., see [[/Writing tips|writing tips]]) * Structure ** Use a logical heading structure that aligns with the focus questions ** Use [https://www.masterclass.com/articles/sentence-case-explained sentence casing] throughout, including for headings and sub-headings ** Use the default heading style (e.g., do not add italics and/or bold) ** Sub-headings are optional *** Avoid having sections with a single sub-heading — each section should contain 0 or 2+ sub-headings. *** If sub-headings are used, provides at least 1 introductory paragraph before branching into sub-sections. * Sentences ** [[w:Narration#Narrative point of view|Narrative point of view]][https://www.grammarly.com/blog/first-second-and-third-person/]: In the main text, use [[w:Narration#Third-person|3rd person perspective]] (e.g., "it", "they"). Where [[w:Aside|aside]]s are used, such as examples, case studies, and feature boxes, [[w:First-person narrative|1st person perspective]] (e.g., "I" and "we") and/or [[w:Narration#Second-person|2nd person perspective]] (e.g., "you") can work well. * Paragraphs ** A well-constructed paragraph is generally 3 to 5 sentences (opening sentence, body sentences, and a concluding/linking sentence). Avoid one-sentence paragraphs and overly long paragraphs. ** Paragraphs flow logically * Use APA style (as much as reasonably possible), paying particular attention to: ** citations ** references (especially capitalisation, italicisation, and providing hyperlinked dois) ** table and figure captions ** quotes (include page numbers) * Citations ** Claims need citations using APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style throughout the chapter — don't mix and match. For most psychology students, APA style will be the choice. ** Maximum of 3 citations per point (i.e., avoid 4 or more citations together). * References ** List all cited academic references in APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style. ** Non-academic sources are not used in references. They can be included in the external links section. ===Learning features (5%)=== * Embed interactive learning features such as scenarios/case studies/examples, feature boxes, figures, quizzes, links to relevant Wikipedia and Wikipedia pages, as well as links to key resources via the "See also" and "External links" sections * Case studies ** Include 1 or more examples, scenarios, or case studies ** They can be true (if so, include citations) or fictional ** Use these examples to enhance understanding of theory, research, focus questions, and/or take-home messages ** Present in a feature box and include a figure ** Consider using a "progressive case study" (i.e., a case study presented in separate parts which describe, for example, the problem, attempt at change, and resolution/outcomes). ** Examples of chapters which make effective use of case studies: *** [[Motivation and emotion/Book/2019/Emotional abuse|emotional abuse]] (2019) *** [[Motivation and emotion/Book/2019/Food and fear|food and fear]] (2019) *** [[Motivation and emotion/Book/2019/Opioid system and human emotion|opioid system and human emotion]] (2019) *** [[Motivation and emotion/Book/2019/Social support and emotion|social support and emotion]] (2019) * [[Motivation and emotion/Wikiversity/Feature box|Feature boxes]] ** Use to highlight key information, but avoid overuse ** There are various ways of creating coloured boxes, but the [[Template:RoundBoxTop|RoundBox]] template is a good option. * [[Motivation and emotion/Wikiversity/Figures|Figures]] ** Include relevant, accompanying figures (e.g., photos, drawings, diagrams) to facilitate readers' understanding of the concepts ** Figures are accompanied by explanatory captions and be cited at least once in the main text ** For more information, see [[Motivation and emotion/Assessment/Chapter/Figures|How to use figures]]). * [[Help:Links|Links]] ** In-text (embedded) links: Key words and concepts are [[Making links|linked]] to Wikipedia articles and/or related book chapters. Provide in-text wiki links the ''first time'' that key concepts are mentioned. For example: *** [[w:Emotion|emotion]] involves physiological, subjective feeling, motivational, and socially expressive aspects. The syntax for creating this link is <nowiki>[[w:Emotion|emotion]]</nowiki>). It is also possible to link to a section on this same page e.g., &lt;nowiki&gt;[[#Overview|Overview]]&lt;nowiki&gt; will link to the Overview section. *** [[Motivation and emotion/Book/2021/Fitspiration and body image|This chapter]] provides an excellent example of embedded links to Wikiversity pages. ** See also *** Provide interwiki links to key related Wikiversity book chapters and/or Wikipedia articles *** Include source in parentheses ** External links *** Provide at least three links to high quality, relevant external resources *** Include author and/or source in parentheses ** Published academic sources belong in References * [[Motivation and emotion/Wikiversity/Tables|Tables]] ** Use accompanying tables to help organise information and communicate concepts to readers ** Tables are accompanied by explanatory APA style captions and are cited in the body text * [[Help:Quiz|Quizzes]] ** Quiz questions or reflection questions encourage reader engagement ** Focus on core concepts (esp. take-home messages) rather than trivia ** Consider incorporating throughout the chapter {{anchor|Socialcontribution}} {{anchor|Social contribution}} ===Social contribution (10%)=== * '''Actions''': Logged contributions which enhance the quality of other book chapters. Useful actions include: ** '''Edits''': Direct edits which improve past or current chapters (e.g., fix errors, enhance clarity) or flag potential improvements by adding [[Template:Clarification templates|clarification templates]]. [[/Search for chapters to improve|Search for chapters to improve]]. ** '''Comments''': Feedback provided on book chapter [[Help:Talk page|talk page]]s ** '''Media uploads''': Upload free-to-use educational images to [[commons:|Wikimedia Commons]] ** '''{{Motivation and emotion/Canvas}} discussion posts''' * '''Evidence''': ** Provide a [[mw:Help:Lists|numbered list]] with summaries of contributions on your [[Help:User page|Wikiversity user page]], and '''direct links''' that show each change or contribution.<!-- To receive credit, contributions must be publicly logged (i.e., log in to Wikiversity so that the edit is recorded with your user name and time-stamp). Summarise each edit on your user page (in a section called "Social contributions") --> ** More info: [[/Summarising social contributions|summarising social contributions]] * '''Marking''' ** Marking of social contributions will be based on a combination of: *** '''Quantity''': **** Breadth: number of chapters contributed to **** Channels: range of communication channels used *** '''Quality''': **** Depth/extent/thoroughness **** Insightfulness **** Practical value *** '''Timeliness''' — there is generally: **** Greater value in earlier contributions **** Lesser value in last-minute contributions ** Marks will be allocated to each clearly evidenced contribution as follows: *** Minor <= 0.25 *** Moderate 0.50 *** Major 1.00 *** Very significant > 1.00 * '''Bonus marks''' ** Up to 5 bonus marks (out of 100 for the book chapter) will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level. ** Approximately 5% of students receive social contribution bonus marks. ** This could include extensive copyediting of multiple chapters and/or regular feedback or support on multiple chapter discussion pages. It may also involve substantial activity on the UCLearn discussion forum. ==Marking rubric== {{Notice|1=[https://docs.google.com/document/d/1yQd1-IekznJNLwhef-yEBaxKtRR6dAVESWXoTa-ti3c/edit?usp=sharing Marking rubric]}} ==Examples== Examples of high quality [[Motivation and emotion/Book|motivation and emotion book chapters]]: * [[Motivation and emotion/Book/2025/AI use, cognitive load, and motivation|AI use, cognitive load, and motivation]] - How does generative AI reduce cognitive effort, and what are the motivational consequences? (2025) * [[Motivation and emotion/Book/2025/Autonomy and intrinsic motivation in self-determination theory|Autonomy and intrinsic motivation in self-determination theory]]: How does autonomy influence intrinsic motivation according to SDT? (2025) * [[Motivation and emotion/Book/2022/Disappointment|Disappointment]]: What is disappointment, what causes it, and how can it be managed? (2022) * [[Motivation and emotion/Book/2016/Illicit drug taking at music festivals|Illicit drug taking at music festivals]]: What motivates young people to take illicit drugs at music festivals? (2016) * [[Motivation and emotion/Book/2019/Organisational change motivation|Organisational change motivation]]: How can leaders build a culture of agility, adaptability, and resilience to deal with a constantly changing workplace? (2019) * [[Motivation and emotion/Book/2019/Phobias|Phobias]]: What are phobias and how can they be dealt with? (2019) * [[Motivation and emotion/Book/2025/Transactive goal dynamics theory and motivation|Transactive goal dynamics theory and motivation]]: What is transactive goal dynamics theory and how does it impact motivation? (2025) Note that as of 2025, chapters no longer include multimedia presentations. For more examples, see the {{Motivation and emotion/Book/High}}s in the [[Motivation and emotion/Book|lists of previous book chapters]]<!-- and the [[:Category:Motivation and emotion/Book/2022/Top|top chapters of 2022]] -->. ==Licensing== Contributions to Wikiversity are made under a [http://creativecommons.org/licenses/by-sa/4.0/ Creative Commons 4.0 Share-alike] (CC-BY-SA 4.0) license which is irrevocable. This license gives permission for others to edit and re-use, with appropriate acknowledgement. For more information, see the [[wmf:Terms of use|Wikimedia Foundation's Terms of use]]. If you do not wish to contribute your work under this license, discuss [[Motivation and emotion/Assessment/Alternative|alternative assessment options]] with the unit convener. ==See also== * [[/FAQ/]] * [[Motivation and emotion/Book|Previous chapters]] * Marking and feedback ** [[Motivation and emotion/Assessment/Chapter/Feedback|General feedback]] ** [[Template:MEBF|Feedback template]] ** [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing Marking rubric] * [[#Socialcontribution|Social contributions]] ** [[/Search for chapters to improve/]] ** [[/Summarising social contributions/]] * [[Motivation and emotion/Tutorials|Tutorials]] <!-- ** [[Motivation and emotion/Tutorials/Topic selection|Tutorial 01: Topic selection]] --> ** [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2: Wiki editing]] ** [[Motivation and emotion/Tutorials/Functionalist theory and self-tracking#Google Scholar|Tutorial 5: Google Scholar]] ** [[Motivation and emotion/Tutorials/Measuring emotion#Topic development feedback|Tutorial 8: Topic development feedback]] * Wikiversity ** [[/Feature boxes/]] ** [[/Figures/]] ** [[How to find free-to-use images|Find free images]] ** [[/Tables/]] * [[/Writing tips/]] ** [[/How to handle a lack of information/|Handling a lack of information]] ** [[/Readability|Readability]] ** [[Motivation and emotion/Assessment/Using generative AI|Using generative AI]] ** [[/Word count|Word count]] {{Motivation and emotion/Assessment/Navigation}} [[Category:Motivation and emotion/Assessment/Chapter| ]] [[Category:Motivation and emotion guidelines]] irl4g5xgj46r7d3h2gqje9luokqzzeu 2835396 2835395 2026-10-01T22:30:24Z Jtneill 10242 /* Length (word count) */ 2835396 wikitext text/x-wiki {{title|Book chapter — Guidelines}} <div style="text-align: center;">''Collaborative online book chapter authoring'' <!-- ---------------------------------- ---> <!-- Count down --> <!-- ---------------------------------- ---><!-- {{countdown |year = 2026 |month = 10 |day = 12 |hour = 0 |event = this assessment is due }} --><!-- {{Motivation and emotion/Assessment/In development}} --> {{/Contents/}}</div> {{TOCright}} ==Overview== * Weight: 50% * Due {{/Due}} * Tasks ** Author an online [[Motivation and emotion/Book|book chapter]] (up to 4,000 words) that explains key psychological theory and research about a unique, specific motivation or emotion topic. ** Develop the chapter by building on the [[Motivation and emotion/Assessment/Topic|topic development]] plan and addressing feedback. ** Contribute to the development of other book chapters (social contribution). * Follow the [[#Instructions|instructions]] and address the [[#Marking criteria|marking criteria]]. ==Purpose== The purpose of the book chapter is to explain and critically evaluate what psychological science says about a specific motivation or emotion topic, and to demonstrate how this knowledge can be applied to understanding and improving human behaviour in everyday life. ==Marking and feedback== * Submissions will be marked according to the [[#Marking criteria|marking criteria]] and [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing marking rubric]. * Marks will be provided via {{Motivation and emotion/Canvas}} when the university releases unit results (see [https://www.canberra.edu.au/about-uc/key-dates/ Key dates]). * Up to 5 bonus marks will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level (see [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60 rubric]). * Written feedback about how well the chapter addresses the marking criteria will be available via the topic's Wikiversity discussion page. * Follow up with the [[Motivation and emotion/About/Staff|unit convener]] if you have any questions. ==Extensions and late submissions== * Apply for extension using the unit's online Extension Application Form (see {{Motivation and emotion/Canvas}}) with appropriate documentary evidence. * Submissions will be accepted up to 3 days late (-10% per day). * If you don't submit this assessment it is unlikely that you will pass the unit. ==Learning outcomes== How the unit's [[Motivation and emotion/About/Learning outcomes|learning outcomes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto; vertical-align:top;" |- | style="width:40%;" | '''Learning outcome''' | style="width:60%;" | '''Assessment task''' |- | style="vertical-align:top;" | Integrate theories and current research towards explaining the role of motivation and emotions in human behaviour. | style="vertical-align:top;" | Use the most relevant theories and peer-reviewed research to explain a specific motivation or emotion topic. |- | style="vertical-align:top;" | Critically apply knowledge of motivation or emotion to an indepth understanding of a specific topic in this field. | style="vertical-align:top;" | Explain how psychological science can be applied to a specific motivation or emotion topic. Use figures, examples, and/or other interactive learning features to illustrate how this knowledge can apply to understanding human behaviour in everyday life. |} ==Graduate attributes== How the unit's [[Motivation and emotion/About/Graduate attributes|graduate attributes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto;" |- ! style="width:20%;" | Category ! style="width:20%;" | Graduate attribute ! style="width:60%;" | Assessment task |- | rowspan="4" style="vertical-align:top;" | '''Be professional''' | style="vertical-align:top;" | Communicate effectively | style="vertical-align:top;" | Review scholarly knowledge in an open, online environment and address feedback. |- | style="vertical-align:top;" | Display initiative and drive | style="vertical-align:top;" | Produce an online book chapter about a novel motivation or emotion topic. |- | style="vertical-align:top;" | Up-to-date knowledge and skills | style="vertical-align:top;" | Utilise the most relevant psychological theory and research to address a practical question. |- | style="vertical-align:top;" | Solve problems via thinking | style="vertical-align:top;" | Use critical thinking to explain how psychological science can address real-world problems. |- | rowspan="3" style="vertical-align:top;" | '''Be a global citizen''' | style="vertical-align:top;" | Informed and balanced | style="vertical-align:top;" | Provide a balanced, critical chapter which is accessible to a lay audience. |- | style="vertical-align:top;" | Communicate diversely | style="vertical-align:top;" | Collaborate with peers to communicate knowledge openly with a global audience. |- | style="vertical-align:top;" | Creative use of technology | style="vertical-align:top;" | Learn how to collaborate using wiki technology. |- | rowspan="2" style="vertical-align:top;" | '''Be a lifelong learner''' | style="vertical-align:top;" | Engage in new ideas | style="vertical-align:top;" | Engage in a collaborative learning culture by incorporating feedback and suggestions. |- | style="vertical-align:top;" | Evaluate and adopt new technology | style="vertical-align:top;" | Experience project work in a collaborative, online editing environment. |} ==Instructions== The book chapter should communicate your understanding of the topic based on the best available psychological theory and research. Explain and apply the most relevant evidence in a clear, engaging, and accessible way. The aim is to demonstrate your ability to synthesise and critically evaluate psychological science in order to understand and respond to a specific motivation or emotion phenomenon. The following instructions should be used to guide the development of the book chapter. ===Theme=== * Chapters should fit the book theme which is "understanding and improving our motivational and emotional lives using psychological science" ===Audience=== * The target audience is a general (non-topic-expert) reader interested in personal growth and development based on knowledge in psychological science (theory and research). This is a [[w:science communication|science communication]] exercise. ===Wikiversity=== * Present the chapter as a single page on the [[Main Page|English Wikiversity]] website. A link to the chapter should appear in the [[Motivation and emotion/Book|table of contents]] along with the lead author's Wikiversity user name ===Topic=== * The title and sub-title must be approved by the [[Motivation and emotion/About/Staff|unit convener]] ===Collaboration and feedback=== * Chapters should be independently developed and written primarily by the lead author, but collaboration is strongly encouraged (e.g., by incorporating useful edits and feedback from others) * [[Motivation and emotion/Assessment/Using generative AI|Generative AI]] may be used with appropriate acknowledgement * Lead authors are encouraged to seek feedback about the chapter during the drafting process (e.g., start a {{Motivation and emotion/Canvas}} discussion thread<!-- (use the chapter title and subtitle in the subject line and include a clickable hyperlink to the chapter in the message)-->) * Feedback is usually best placed on the chapter's wiki discussion page * Feedback on the [[Motivation and emotion/Assessment/Topic|topic development]] (chapter plan) will be provided by the [[Motivation and emotion/About/Staff|unit convener]] ===Length (word count)=== {{Anchor|Wordcount}}{{Anchor|Word count}} * There is no minimum length * Maximum 4,000 words ** There is no additional 10% allowance ** Words beyond the maximum will not be considered for marking purposes * What to count: (** Count everything from top to bottom of the editable page (in view mode, not edit mode) including the title, subtitle, headings, text, citations, tables, figures, references, see also, and external links *** Don't count menu text across the top and down the left, or categories at the bottom ** How to count: *** Google Chrome extension: [https://chromewebstore.google.com/detail/word-counter/cbjddaobmdfhbfgdgjocbhklpmclcboe Word Counter]. This extension is probably the easiest reliable method for counting words on a Wikiversity page. However, UC recently started blocking this extension on UC devices. *** Website: Paste the URL into [https://hsuper.tools/web-page-word-counter Webpage Word Counter] (it overcounts by ~100 words because it includes menus etc.) *** Word processor: Cut and paste into a word processor (i.e., copy starting at title and finishing with the last external link) * If the chapter exceeds the maximum word count, see [[/Word count|these suggestions]] for strategies to reduce the length while retaining the key content. ===Submission=== * Submit the chapter URL (website address), your Wikiversity user name, and a PDF of the chapter via {{Motivation and emotion/Canvas}} ==Marking criteria== [[File:Balanced scales.svg|right|125px]] Book chapters will be marked against the following criteria. ===Overview (5%)=== * Scenario: Provide an engaging scenario or case study in a feature box, with an illustrative figure * Problem statement: Easy to read and understand outline of the key concepts and explanation of practical/real-world problem to be solved * Focus questions: Establish [[/Focus questions|focus questions]] which align with the sub-title and subsequent heading structure ===Theory (20%)=== * Clearly explain the theoretical framework for understanding the topic * Select the most relevant psychological theories/models that apply to the problem. Depending on the topic, this may involve focusing on a single theory or comparing and contrasting two or more theories. * Use at least the best dozen or so peer-reviewed theory references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Clearly explain and apply the theory(ies) * Include illustrative examples, such as case studies * Demonstrate a critical perspective ===Research (25%)=== * Clearly explain how key, peer-reviewed research findings apply to the problem * Use at least the best dozen or so peer-reviewed research references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Include relevant major reviews (such as systematic reviews and meta-analyses) * [[w:Critical thinking|Critical analyse]] the key research findings, including limitations and implications ===Integration (10%)=== * Integrate discussion of theory and review of relevant research * Use research to critically inform interpretation and application of the theory(ies) ===Conclusion (5%)=== * Clear and concise communication of key points and take-home messages * Aligned with the subtitle and focus questions, with implications for the [[Motivation and emotion/Book/Theme|book theme]] ===Style (20%)=== * Overall ** Present and illustrate the problem and knowledge in an interesting way, using a logical structure, clear layout, correct spelling and grammar, and [[APA style]] ** [[/Readability|Readable]] for a layperson interested in psychological science ** Address the [[#Theme|book theme]] by providing practical, academically sound, self-improvement information ** Address an international audience (i.e., avoid an overly local or national perspective) ** Use default wiki style for paragraph alignment, font colour, type, and size, and heading styles ** Use Australian spelling (e.g., hypothesise, behaviour, fulfilment) rather than American spelling (e.g., hypothesize, behavior, fulfillment) ** Correct grammar (e.g., see [[/Writing tips|writing tips]]) * Structure ** Use a logical heading structure that aligns with the focus questions ** Use [https://www.masterclass.com/articles/sentence-case-explained sentence casing] throughout, including for headings and sub-headings ** Use the default heading style (e.g., do not add italics and/or bold) ** Sub-headings are optional *** Avoid having sections with a single sub-heading — each section should contain 0 or 2+ sub-headings. *** If sub-headings are used, provides at least 1 introductory paragraph before branching into sub-sections. * Sentences ** [[w:Narration#Narrative point of view|Narrative point of view]][https://www.grammarly.com/blog/first-second-and-third-person/]: In the main text, use [[w:Narration#Third-person|3rd person perspective]] (e.g., "it", "they"). Where [[w:Aside|aside]]s are used, such as examples, case studies, and feature boxes, [[w:First-person narrative|1st person perspective]] (e.g., "I" and "we") and/or [[w:Narration#Second-person|2nd person perspective]] (e.g., "you") can work well. * Paragraphs ** A well-constructed paragraph is generally 3 to 5 sentences (opening sentence, body sentences, and a concluding/linking sentence). Avoid one-sentence paragraphs and overly long paragraphs. ** Paragraphs flow logically * Use APA style (as much as reasonably possible), paying particular attention to: ** citations ** references (especially capitalisation, italicisation, and providing hyperlinked dois) ** table and figure captions ** quotes (include page numbers) * Citations ** Claims need citations using APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style throughout the chapter — don't mix and match. For most psychology students, APA style will be the choice. ** Maximum of 3 citations per point (i.e., avoid 4 or more citations together). * References ** List all cited academic references in APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style. ** Non-academic sources are not used in references. They can be included in the external links section. ===Learning features (5%)=== * Embed interactive learning features such as scenarios/case studies/examples, feature boxes, figures, quizzes, links to relevant Wikipedia and Wikipedia pages, as well as links to key resources via the "See also" and "External links" sections * Case studies ** Include 1 or more examples, scenarios, or case studies ** They can be true (if so, include citations) or fictional ** Use these examples to enhance understanding of theory, research, focus questions, and/or take-home messages ** Present in a feature box and include a figure ** Consider using a "progressive case study" (i.e., a case study presented in separate parts which describe, for example, the problem, attempt at change, and resolution/outcomes). ** Examples of chapters which make effective use of case studies: *** [[Motivation and emotion/Book/2019/Emotional abuse|emotional abuse]] (2019) *** [[Motivation and emotion/Book/2019/Food and fear|food and fear]] (2019) *** [[Motivation and emotion/Book/2019/Opioid system and human emotion|opioid system and human emotion]] (2019) *** [[Motivation and emotion/Book/2019/Social support and emotion|social support and emotion]] (2019) * [[Motivation and emotion/Wikiversity/Feature box|Feature boxes]] ** Use to highlight key information, but avoid overuse ** There are various ways of creating coloured boxes, but the [[Template:RoundBoxTop|RoundBox]] template is a good option. * [[Motivation and emotion/Wikiversity/Figures|Figures]] ** Include relevant, accompanying figures (e.g., photos, drawings, diagrams) to facilitate readers' understanding of the concepts ** Figures are accompanied by explanatory captions and be cited at least once in the main text ** For more information, see [[Motivation and emotion/Assessment/Chapter/Figures|How to use figures]]). * [[Help:Links|Links]] ** In-text (embedded) links: Key words and concepts are [[Making links|linked]] to Wikipedia articles and/or related book chapters. Provide in-text wiki links the ''first time'' that key concepts are mentioned. For example: *** [[w:Emotion|emotion]] involves physiological, subjective feeling, motivational, and socially expressive aspects. The syntax for creating this link is <nowiki>[[w:Emotion|emotion]]</nowiki>). It is also possible to link to a section on this same page e.g., &lt;nowiki&gt;[[#Overview|Overview]]&lt;nowiki&gt; will link to the Overview section. *** [[Motivation and emotion/Book/2021/Fitspiration and body image|This chapter]] provides an excellent example of embedded links to Wikiversity pages. ** See also *** Provide interwiki links to key related Wikiversity book chapters and/or Wikipedia articles *** Include source in parentheses ** External links *** Provide at least three links to high quality, relevant external resources *** Include author and/or source in parentheses ** Published academic sources belong in References * [[Motivation and emotion/Wikiversity/Tables|Tables]] ** Use accompanying tables to help organise information and communicate concepts to readers ** Tables are accompanied by explanatory APA style captions and are cited in the body text * [[Help:Quiz|Quizzes]] ** Quiz questions or reflection questions encourage reader engagement ** Focus on core concepts (esp. take-home messages) rather than trivia ** Consider incorporating throughout the chapter {{anchor|Socialcontribution}} {{anchor|Social contribution}} ===Social contribution (10%)=== * '''Actions''': Logged contributions which enhance the quality of other book chapters. Useful actions include: ** '''Edits''': Direct edits which improve past or current chapters (e.g., fix errors, enhance clarity) or flag potential improvements by adding [[Template:Clarification templates|clarification templates]]. [[/Search for chapters to improve|Search for chapters to improve]]. ** '''Comments''': Feedback provided on book chapter [[Help:Talk page|talk page]]s ** '''Media uploads''': Upload free-to-use educational images to [[commons:|Wikimedia Commons]] ** '''{{Motivation and emotion/Canvas}} discussion posts''' * '''Evidence''': ** Provide a [[mw:Help:Lists|numbered list]] with summaries of contributions on your [[Help:User page|Wikiversity user page]], and '''direct links''' that show each change or contribution.<!-- To receive credit, contributions must be publicly logged (i.e., log in to Wikiversity so that the edit is recorded with your user name and time-stamp). Summarise each edit on your user page (in a section called "Social contributions") --> ** More info: [[/Summarising social contributions|summarising social contributions]] * '''Marking''' ** Marking of social contributions will be based on a combination of: *** '''Quantity''': **** Breadth: number of chapters contributed to **** Channels: range of communication channels used *** '''Quality''': **** Depth/extent/thoroughness **** Insightfulness **** Practical value *** '''Timeliness''' — there is generally: **** Greater value in earlier contributions **** Lesser value in last-minute contributions ** Marks will be allocated to each clearly evidenced contribution as follows: *** Minor <= 0.25 *** Moderate 0.50 *** Major 1.00 *** Very significant > 1.00 * '''Bonus marks''' ** Up to 5 bonus marks (out of 100 for the book chapter) will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level. ** Approximately 5% of students receive social contribution bonus marks. ** This could include extensive copyediting of multiple chapters and/or regular feedback or support on multiple chapter discussion pages. It may also involve substantial activity on the UCLearn discussion forum. ==Marking rubric== {{Notice|1=[https://docs.google.com/document/d/1yQd1-IekznJNLwhef-yEBaxKtRR6dAVESWXoTa-ti3c/edit?usp=sharing Marking rubric]}} ==Examples== Examples of high quality [[Motivation and emotion/Book|motivation and emotion book chapters]]: * [[Motivation and emotion/Book/2025/AI use, cognitive load, and motivation|AI use, cognitive load, and motivation]] - How does generative AI reduce cognitive effort, and what are the motivational consequences? (2025) * [[Motivation and emotion/Book/2025/Autonomy and intrinsic motivation in self-determination theory|Autonomy and intrinsic motivation in self-determination theory]]: How does autonomy influence intrinsic motivation according to SDT? (2025) * [[Motivation and emotion/Book/2022/Disappointment|Disappointment]]: What is disappointment, what causes it, and how can it be managed? (2022) * [[Motivation and emotion/Book/2016/Illicit drug taking at music festivals|Illicit drug taking at music festivals]]: What motivates young people to take illicit drugs at music festivals? (2016) * [[Motivation and emotion/Book/2019/Organisational change motivation|Organisational change motivation]]: How can leaders build a culture of agility, adaptability, and resilience to deal with a constantly changing workplace? (2019) * [[Motivation and emotion/Book/2019/Phobias|Phobias]]: What are phobias and how can they be dealt with? (2019) * [[Motivation and emotion/Book/2025/Transactive goal dynamics theory and motivation|Transactive goal dynamics theory and motivation]]: What is transactive goal dynamics theory and how does it impact motivation? (2025) Note that as of 2025, chapters no longer include multimedia presentations. For more examples, see the {{Motivation and emotion/Book/High}}s in the [[Motivation and emotion/Book|lists of previous book chapters]]<!-- and the [[:Category:Motivation and emotion/Book/2022/Top|top chapters of 2022]] -->. ==Licensing== Contributions to Wikiversity are made under a [http://creativecommons.org/licenses/by-sa/4.0/ Creative Commons 4.0 Share-alike] (CC-BY-SA 4.0) license which is irrevocable. This license gives permission for others to edit and re-use, with appropriate acknowledgement. For more information, see the [[wmf:Terms of use|Wikimedia Foundation's Terms of use]]. If you do not wish to contribute your work under this license, discuss [[Motivation and emotion/Assessment/Alternative|alternative assessment options]] with the unit convener. ==See also== * [[/FAQ/]] * [[Motivation and emotion/Book|Previous chapters]] * Marking and feedback ** [[Motivation and emotion/Assessment/Chapter/Feedback|General feedback]] ** [[Template:MEBF|Feedback template]] ** [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing Marking rubric] * [[#Socialcontribution|Social contributions]] ** [[/Search for chapters to improve/]] ** [[/Summarising social contributions/]] * [[Motivation and emotion/Tutorials|Tutorials]] <!-- ** [[Motivation and emotion/Tutorials/Topic selection|Tutorial 01: Topic selection]] --> ** [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2: Wiki editing]] ** [[Motivation and emotion/Tutorials/Functionalist theory and self-tracking#Google Scholar|Tutorial 5: Google Scholar]] ** [[Motivation and emotion/Tutorials/Measuring emotion#Topic development feedback|Tutorial 8: Topic development feedback]] * Wikiversity ** [[/Feature boxes/]] ** [[/Figures/]] ** [[How to find free-to-use images|Find free images]] ** [[/Tables/]] * [[/Writing tips/]] ** [[/How to handle a lack of information/|Handling a lack of information]] ** [[/Readability|Readability]] ** [[Motivation and emotion/Assessment/Using generative AI|Using generative AI]] ** [[/Word count|Word count]] {{Motivation and emotion/Assessment/Navigation}} [[Category:Motivation and emotion/Assessment/Chapter| ]] [[Category:Motivation and emotion guidelines]] ot95rws7pzucneqbvf9nmw08uv0h2l7 2835398 2835396 2026-10-01T22:30:44Z Jtneill 10242 /* Length (word count) */ 2835398 wikitext text/x-wiki {{title|Book chapter — Guidelines}} <div style="text-align: center;">''Collaborative online book chapter authoring'' <!-- ---------------------------------- ---> <!-- Count down --> <!-- ---------------------------------- ---><!-- {{countdown |year = 2026 |month = 10 |day = 12 |hour = 0 |event = this assessment is due }} --><!-- {{Motivation and emotion/Assessment/In development}} --> {{/Contents/}}</div> {{TOCright}} ==Overview== * Weight: 50% * Due {{/Due}} * Tasks ** Author an online [[Motivation and emotion/Book|book chapter]] (up to 4,000 words) that explains key psychological theory and research about a unique, specific motivation or emotion topic. ** Develop the chapter by building on the [[Motivation and emotion/Assessment/Topic|topic development]] plan and addressing feedback. ** Contribute to the development of other book chapters (social contribution). * Follow the [[#Instructions|instructions]] and address the [[#Marking criteria|marking criteria]]. ==Purpose== The purpose of the book chapter is to explain and critically evaluate what psychological science says about a specific motivation or emotion topic, and to demonstrate how this knowledge can be applied to understanding and improving human behaviour in everyday life. ==Marking and feedback== * Submissions will be marked according to the [[#Marking criteria|marking criteria]] and [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing marking rubric]. * Marks will be provided via {{Motivation and emotion/Canvas}} when the university releases unit results (see [https://www.canberra.edu.au/about-uc/key-dates/ Key dates]). * Up to 5 bonus marks will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level (see [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60 rubric]). * Written feedback about how well the chapter addresses the marking criteria will be available via the topic's Wikiversity discussion page. * Follow up with the [[Motivation and emotion/About/Staff|unit convener]] if you have any questions. ==Extensions and late submissions== * Apply for extension using the unit's online Extension Application Form (see {{Motivation and emotion/Canvas}}) with appropriate documentary evidence. * Submissions will be accepted up to 3 days late (-10% per day). * If you don't submit this assessment it is unlikely that you will pass the unit. ==Learning outcomes== How the unit's [[Motivation and emotion/About/Learning outcomes|learning outcomes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto; vertical-align:top;" |- | style="width:40%;" | '''Learning outcome''' | style="width:60%;" | '''Assessment task''' |- | style="vertical-align:top;" | Integrate theories and current research towards explaining the role of motivation and emotions in human behaviour. | style="vertical-align:top;" | Use the most relevant theories and peer-reviewed research to explain a specific motivation or emotion topic. |- | style="vertical-align:top;" | Critically apply knowledge of motivation or emotion to an indepth understanding of a specific topic in this field. | style="vertical-align:top;" | Explain how psychological science can be applied to a specific motivation or emotion topic. Use figures, examples, and/or other interactive learning features to illustrate how this knowledge can apply to understanding human behaviour in everyday life. |} ==Graduate attributes== How the unit's [[Motivation and emotion/About/Graduate attributes|graduate attributes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto;" |- ! style="width:20%;" | Category ! style="width:20%;" | Graduate attribute ! style="width:60%;" | Assessment task |- | rowspan="4" style="vertical-align:top;" | '''Be professional''' | style="vertical-align:top;" | Communicate effectively | style="vertical-align:top;" | Review scholarly knowledge in an open, online environment and address feedback. |- | style="vertical-align:top;" | Display initiative and drive | style="vertical-align:top;" | Produce an online book chapter about a novel motivation or emotion topic. |- | style="vertical-align:top;" | Up-to-date knowledge and skills | style="vertical-align:top;" | Utilise the most relevant psychological theory and research to address a practical question. |- | style="vertical-align:top;" | Solve problems via thinking | style="vertical-align:top;" | Use critical thinking to explain how psychological science can address real-world problems. |- | rowspan="3" style="vertical-align:top;" | '''Be a global citizen''' | style="vertical-align:top;" | Informed and balanced | style="vertical-align:top;" | Provide a balanced, critical chapter which is accessible to a lay audience. |- | style="vertical-align:top;" | Communicate diversely | style="vertical-align:top;" | Collaborate with peers to communicate knowledge openly with a global audience. |- | style="vertical-align:top;" | Creative use of technology | style="vertical-align:top;" | Learn how to collaborate using wiki technology. |- | rowspan="2" style="vertical-align:top;" | '''Be a lifelong learner''' | style="vertical-align:top;" | Engage in new ideas | style="vertical-align:top;" | Engage in a collaborative learning culture by incorporating feedback and suggestions. |- | style="vertical-align:top;" | Evaluate and adopt new technology | style="vertical-align:top;" | Experience project work in a collaborative, online editing environment. |} ==Instructions== The book chapter should communicate your understanding of the topic based on the best available psychological theory and research. Explain and apply the most relevant evidence in a clear, engaging, and accessible way. The aim is to demonstrate your ability to synthesise and critically evaluate psychological science in order to understand and respond to a specific motivation or emotion phenomenon. The following instructions should be used to guide the development of the book chapter. ===Theme=== * Chapters should fit the book theme which is "understanding and improving our motivational and emotional lives using psychological science" ===Audience=== * The target audience is a general (non-topic-expert) reader interested in personal growth and development based on knowledge in psychological science (theory and research). This is a [[w:science communication|science communication]] exercise. ===Wikiversity=== * Present the chapter as a single page on the [[Main Page|English Wikiversity]] website. A link to the chapter should appear in the [[Motivation and emotion/Book|table of contents]] along with the lead author's Wikiversity user name ===Topic=== * The title and sub-title must be approved by the [[Motivation and emotion/About/Staff|unit convener]] ===Collaboration and feedback=== * Chapters should be independently developed and written primarily by the lead author, but collaboration is strongly encouraged (e.g., by incorporating useful edits and feedback from others) * [[Motivation and emotion/Assessment/Using generative AI|Generative AI]] may be used with appropriate acknowledgement * Lead authors are encouraged to seek feedback about the chapter during the drafting process (e.g., start a {{Motivation and emotion/Canvas}} discussion thread<!-- (use the chapter title and subtitle in the subject line and include a clickable hyperlink to the chapter in the message)-->) * Feedback is usually best placed on the chapter's wiki discussion page * Feedback on the [[Motivation and emotion/Assessment/Topic|topic development]] (chapter plan) will be provided by the [[Motivation and emotion/About/Staff|unit convener]] ===Length (word count)=== {{Anchor|Wordcount}}{{Anchor|Word count}} * There is no minimum length * Maximum 4,000 words ** There is no additional 10% allowance ** Words beyond the maximum will not be considered for marking purposes * What to count: *** Count everything from top to bottom of the editable page (in view mode, not edit mode) including the title, subtitle, headings, text, citations, tables, figures, references, see also, and external links *** Don't count menu text across the top and down the left, or categories at the bottom ** How to count: *** Google Chrome extension: [https://chromewebstore.google.com/detail/word-counter/cbjddaobmdfhbfgdgjocbhklpmclcboe Word Counter]. This extension is probably the easiest reliable method for counting words on a Wikiversity page. However, UC recently started blocking this extension on UC devices. *** Website: Paste the URL into [https://hsuper.tools/web-page-word-counter Webpage Word Counter] (it overcounts by ~100 words because it includes menus etc.) *** Word processor: Cut and paste into a word processor (i.e., copy starting at title and finishing with the last external link) * If the chapter exceeds the maximum word count, see [[/Word count|these suggestions]] for strategies to reduce the length while retaining the key content. ===Submission=== * Submit the chapter URL (website address), your Wikiversity user name, and a PDF of the chapter via {{Motivation and emotion/Canvas}} ==Marking criteria== [[File:Balanced scales.svg|right|125px]] Book chapters will be marked against the following criteria. ===Overview (5%)=== * Scenario: Provide an engaging scenario or case study in a feature box, with an illustrative figure * Problem statement: Easy to read and understand outline of the key concepts and explanation of practical/real-world problem to be solved * Focus questions: Establish [[/Focus questions|focus questions]] which align with the sub-title and subsequent heading structure ===Theory (20%)=== * Clearly explain the theoretical framework for understanding the topic * Select the most relevant psychological theories/models that apply to the problem. Depending on the topic, this may involve focusing on a single theory or comparing and contrasting two or more theories. * Use at least the best dozen or so peer-reviewed theory references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Clearly explain and apply the theory(ies) * Include illustrative examples, such as case studies * Demonstrate a critical perspective ===Research (25%)=== * Clearly explain how key, peer-reviewed research findings apply to the problem * Use at least the best dozen or so peer-reviewed research references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Include relevant major reviews (such as systematic reviews and meta-analyses) * [[w:Critical thinking|Critical analyse]] the key research findings, including limitations and implications ===Integration (10%)=== * Integrate discussion of theory and review of relevant research * Use research to critically inform interpretation and application of the theory(ies) ===Conclusion (5%)=== * Clear and concise communication of key points and take-home messages * Aligned with the subtitle and focus questions, with implications for the [[Motivation and emotion/Book/Theme|book theme]] ===Style (20%)=== * Overall ** Present and illustrate the problem and knowledge in an interesting way, using a logical structure, clear layout, correct spelling and grammar, and [[APA style]] ** [[/Readability|Readable]] for a layperson interested in psychological science ** Address the [[#Theme|book theme]] by providing practical, academically sound, self-improvement information ** Address an international audience (i.e., avoid an overly local or national perspective) ** Use default wiki style for paragraph alignment, font colour, type, and size, and heading styles ** Use Australian spelling (e.g., hypothesise, behaviour, fulfilment) rather than American spelling (e.g., hypothesize, behavior, fulfillment) ** Correct grammar (e.g., see [[/Writing tips|writing tips]]) * Structure ** Use a logical heading structure that aligns with the focus questions ** Use [https://www.masterclass.com/articles/sentence-case-explained sentence casing] throughout, including for headings and sub-headings ** Use the default heading style (e.g., do not add italics and/or bold) ** Sub-headings are optional *** Avoid having sections with a single sub-heading — each section should contain 0 or 2+ sub-headings. *** If sub-headings are used, provides at least 1 introductory paragraph before branching into sub-sections. * Sentences ** [[w:Narration#Narrative point of view|Narrative point of view]][https://www.grammarly.com/blog/first-second-and-third-person/]: In the main text, use [[w:Narration#Third-person|3rd person perspective]] (e.g., "it", "they"). Where [[w:Aside|aside]]s are used, such as examples, case studies, and feature boxes, [[w:First-person narrative|1st person perspective]] (e.g., "I" and "we") and/or [[w:Narration#Second-person|2nd person perspective]] (e.g., "you") can work well. * Paragraphs ** A well-constructed paragraph is generally 3 to 5 sentences (opening sentence, body sentences, and a concluding/linking sentence). Avoid one-sentence paragraphs and overly long paragraphs. ** Paragraphs flow logically * Use APA style (as much as reasonably possible), paying particular attention to: ** citations ** references (especially capitalisation, italicisation, and providing hyperlinked dois) ** table and figure captions ** quotes (include page numbers) * Citations ** Claims need citations using APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style throughout the chapter — don't mix and match. For most psychology students, APA style will be the choice. ** Maximum of 3 citations per point (i.e., avoid 4 or more citations together). * References ** List all cited academic references in APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style. ** Non-academic sources are not used in references. They can be included in the external links section. ===Learning features (5%)=== * Embed interactive learning features such as scenarios/case studies/examples, feature boxes, figures, quizzes, links to relevant Wikipedia and Wikipedia pages, as well as links to key resources via the "See also" and "External links" sections * Case studies ** Include 1 or more examples, scenarios, or case studies ** They can be true (if so, include citations) or fictional ** Use these examples to enhance understanding of theory, research, focus questions, and/or take-home messages ** Present in a feature box and include a figure ** Consider using a "progressive case study" (i.e., a case study presented in separate parts which describe, for example, the problem, attempt at change, and resolution/outcomes). ** Examples of chapters which make effective use of case studies: *** [[Motivation and emotion/Book/2019/Emotional abuse|emotional abuse]] (2019) *** [[Motivation and emotion/Book/2019/Food and fear|food and fear]] (2019) *** [[Motivation and emotion/Book/2019/Opioid system and human emotion|opioid system and human emotion]] (2019) *** [[Motivation and emotion/Book/2019/Social support and emotion|social support and emotion]] (2019) * [[Motivation and emotion/Wikiversity/Feature box|Feature boxes]] ** Use to highlight key information, but avoid overuse ** There are various ways of creating coloured boxes, but the [[Template:RoundBoxTop|RoundBox]] template is a good option. * [[Motivation and emotion/Wikiversity/Figures|Figures]] ** Include relevant, accompanying figures (e.g., photos, drawings, diagrams) to facilitate readers' understanding of the concepts ** Figures are accompanied by explanatory captions and be cited at least once in the main text ** For more information, see [[Motivation and emotion/Assessment/Chapter/Figures|How to use figures]]). * [[Help:Links|Links]] ** In-text (embedded) links: Key words and concepts are [[Making links|linked]] to Wikipedia articles and/or related book chapters. Provide in-text wiki links the ''first time'' that key concepts are mentioned. For example: *** [[w:Emotion|emotion]] involves physiological, subjective feeling, motivational, and socially expressive aspects. The syntax for creating this link is <nowiki>[[w:Emotion|emotion]]</nowiki>). It is also possible to link to a section on this same page e.g., &lt;nowiki&gt;[[#Overview|Overview]]&lt;nowiki&gt; will link to the Overview section. *** [[Motivation and emotion/Book/2021/Fitspiration and body image|This chapter]] provides an excellent example of embedded links to Wikiversity pages. ** See also *** Provide interwiki links to key related Wikiversity book chapters and/or Wikipedia articles *** Include source in parentheses ** External links *** Provide at least three links to high quality, relevant external resources *** Include author and/or source in parentheses ** Published academic sources belong in References * [[Motivation and emotion/Wikiversity/Tables|Tables]] ** Use accompanying tables to help organise information and communicate concepts to readers ** Tables are accompanied by explanatory APA style captions and are cited in the body text * [[Help:Quiz|Quizzes]] ** Quiz questions or reflection questions encourage reader engagement ** Focus on core concepts (esp. take-home messages) rather than trivia ** Consider incorporating throughout the chapter {{anchor|Socialcontribution}} {{anchor|Social contribution}} ===Social contribution (10%)=== * '''Actions''': Logged contributions which enhance the quality of other book chapters. Useful actions include: ** '''Edits''': Direct edits which improve past or current chapters (e.g., fix errors, enhance clarity) or flag potential improvements by adding [[Template:Clarification templates|clarification templates]]. [[/Search for chapters to improve|Search for chapters to improve]]. ** '''Comments''': Feedback provided on book chapter [[Help:Talk page|talk page]]s ** '''Media uploads''': Upload free-to-use educational images to [[commons:|Wikimedia Commons]] ** '''{{Motivation and emotion/Canvas}} discussion posts''' * '''Evidence''': ** Provide a [[mw:Help:Lists|numbered list]] with summaries of contributions on your [[Help:User page|Wikiversity user page]], and '''direct links''' that show each change or contribution.<!-- To receive credit, contributions must be publicly logged (i.e., log in to Wikiversity so that the edit is recorded with your user name and time-stamp). Summarise each edit on your user page (in a section called "Social contributions") --> ** More info: [[/Summarising social contributions|summarising social contributions]] * '''Marking''' ** Marking of social contributions will be based on a combination of: *** '''Quantity''': **** Breadth: number of chapters contributed to **** Channels: range of communication channels used *** '''Quality''': **** Depth/extent/thoroughness **** Insightfulness **** Practical value *** '''Timeliness''' — there is generally: **** Greater value in earlier contributions **** Lesser value in last-minute contributions ** Marks will be allocated to each clearly evidenced contribution as follows: *** Minor <= 0.25 *** Moderate 0.50 *** Major 1.00 *** Very significant > 1.00 * '''Bonus marks''' ** Up to 5 bonus marks (out of 100 for the book chapter) will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level. ** Approximately 5% of students receive social contribution bonus marks. ** This could include extensive copyediting of multiple chapters and/or regular feedback or support on multiple chapter discussion pages. It may also involve substantial activity on the UCLearn discussion forum. ==Marking rubric== {{Notice|1=[https://docs.google.com/document/d/1yQd1-IekznJNLwhef-yEBaxKtRR6dAVESWXoTa-ti3c/edit?usp=sharing Marking rubric]}} ==Examples== Examples of high quality [[Motivation and emotion/Book|motivation and emotion book chapters]]: * [[Motivation and emotion/Book/2025/AI use, cognitive load, and motivation|AI use, cognitive load, and motivation]] - How does generative AI reduce cognitive effort, and what are the motivational consequences? (2025) * [[Motivation and emotion/Book/2025/Autonomy and intrinsic motivation in self-determination theory|Autonomy and intrinsic motivation in self-determination theory]]: How does autonomy influence intrinsic motivation according to SDT? (2025) * [[Motivation and emotion/Book/2022/Disappointment|Disappointment]]: What is disappointment, what causes it, and how can it be managed? (2022) * [[Motivation and emotion/Book/2016/Illicit drug taking at music festivals|Illicit drug taking at music festivals]]: What motivates young people to take illicit drugs at music festivals? (2016) * [[Motivation and emotion/Book/2019/Organisational change motivation|Organisational change motivation]]: How can leaders build a culture of agility, adaptability, and resilience to deal with a constantly changing workplace? (2019) * [[Motivation and emotion/Book/2019/Phobias|Phobias]]: What are phobias and how can they be dealt with? (2019) * [[Motivation and emotion/Book/2025/Transactive goal dynamics theory and motivation|Transactive goal dynamics theory and motivation]]: What is transactive goal dynamics theory and how does it impact motivation? (2025) Note that as of 2025, chapters no longer include multimedia presentations. For more examples, see the {{Motivation and emotion/Book/High}}s in the [[Motivation and emotion/Book|lists of previous book chapters]]<!-- and the [[:Category:Motivation and emotion/Book/2022/Top|top chapters of 2022]] -->. ==Licensing== Contributions to Wikiversity are made under a [http://creativecommons.org/licenses/by-sa/4.0/ Creative Commons 4.0 Share-alike] (CC-BY-SA 4.0) license which is irrevocable. This license gives permission for others to edit and re-use, with appropriate acknowledgement. For more information, see the [[wmf:Terms of use|Wikimedia Foundation's Terms of use]]. If you do not wish to contribute your work under this license, discuss [[Motivation and emotion/Assessment/Alternative|alternative assessment options]] with the unit convener. ==See also== * [[/FAQ/]] * [[Motivation and emotion/Book|Previous chapters]] * Marking and feedback ** [[Motivation and emotion/Assessment/Chapter/Feedback|General feedback]] ** [[Template:MEBF|Feedback template]] ** [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing Marking rubric] * [[#Socialcontribution|Social contributions]] ** [[/Search for chapters to improve/]] ** [[/Summarising social contributions/]] * [[Motivation and emotion/Tutorials|Tutorials]] <!-- ** [[Motivation and emotion/Tutorials/Topic selection|Tutorial 01: Topic selection]] --> ** [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2: Wiki editing]] ** [[Motivation and emotion/Tutorials/Functionalist theory and self-tracking#Google Scholar|Tutorial 5: Google Scholar]] ** [[Motivation and emotion/Tutorials/Measuring emotion#Topic development feedback|Tutorial 8: Topic development feedback]] * Wikiversity ** [[/Feature boxes/]] ** [[/Figures/]] ** [[How to find free-to-use images|Find free images]] ** [[/Tables/]] * [[/Writing tips/]] ** [[/How to handle a lack of information/|Handling a lack of information]] ** [[/Readability|Readability]] ** [[Motivation and emotion/Assessment/Using generative AI|Using generative AI]] ** [[/Word count|Word count]] {{Motivation and emotion/Assessment/Navigation}} [[Category:Motivation and emotion/Assessment/Chapter| ]] [[Category:Motivation and emotion guidelines]] eob3wxteghsvvzn36r57kgy05mn26ap 2835399 2835398 2026-10-01T22:32:07Z Jtneill 10242 /* Length (word count) */ 2835399 wikitext text/x-wiki {{title|Book chapter — Guidelines}} <div style="text-align: center;">''Collaborative online book chapter authoring'' <!-- ---------------------------------- ---> <!-- Count down --> <!-- ---------------------------------- ---><!-- {{countdown |year = 2026 |month = 10 |day = 12 |hour = 0 |event = this assessment is due }} --><!-- {{Motivation and emotion/Assessment/In development}} --> {{/Contents/}}</div> {{TOCright}} ==Overview== * Weight: 50% * Due {{/Due}} * Tasks ** Author an online [[Motivation and emotion/Book|book chapter]] (up to 4,000 words) that explains key psychological theory and research about a unique, specific motivation or emotion topic. ** Develop the chapter by building on the [[Motivation and emotion/Assessment/Topic|topic development]] plan and addressing feedback. ** Contribute to the development of other book chapters (social contribution). * Follow the [[#Instructions|instructions]] and address the [[#Marking criteria|marking criteria]]. ==Purpose== The purpose of the book chapter is to explain and critically evaluate what psychological science says about a specific motivation or emotion topic, and to demonstrate how this knowledge can be applied to understanding and improving human behaviour in everyday life. ==Marking and feedback== * Submissions will be marked according to the [[#Marking criteria|marking criteria]] and [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing marking rubric]. * Marks will be provided via {{Motivation and emotion/Canvas}} when the university releases unit results (see [https://www.canberra.edu.au/about-uc/key-dates/ Key dates]). * Up to 5 bonus marks will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level (see [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60 rubric]). * Written feedback about how well the chapter addresses the marking criteria will be available via the topic's Wikiversity discussion page. * Follow up with the [[Motivation and emotion/About/Staff|unit convener]] if you have any questions. ==Extensions and late submissions== * Apply for extension using the unit's online Extension Application Form (see {{Motivation and emotion/Canvas}}) with appropriate documentary evidence. * Submissions will be accepted up to 3 days late (-10% per day). * If you don't submit this assessment it is unlikely that you will pass the unit. ==Learning outcomes== How the unit's [[Motivation and emotion/About/Learning outcomes|learning outcomes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto; vertical-align:top;" |- | style="width:40%;" | '''Learning outcome''' | style="width:60%;" | '''Assessment task''' |- | style="vertical-align:top;" | Integrate theories and current research towards explaining the role of motivation and emotions in human behaviour. | style="vertical-align:top;" | Use the most relevant theories and peer-reviewed research to explain a specific motivation or emotion topic. |- | style="vertical-align:top;" | Critically apply knowledge of motivation or emotion to an indepth understanding of a specific topic in this field. | style="vertical-align:top;" | Explain how psychological science can be applied to a specific motivation or emotion topic. Use figures, examples, and/or other interactive learning features to illustrate how this knowledge can apply to understanding human behaviour in everyday life. |} ==Graduate attributes== How the unit's [[Motivation and emotion/About/Graduate attributes|graduate attributes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto;" |- ! style="width:20%;" | Category ! style="width:20%;" | Graduate attribute ! style="width:60%;" | Assessment task |- | rowspan="4" style="vertical-align:top;" | '''Be professional''' | style="vertical-align:top;" | Communicate effectively | style="vertical-align:top;" | Review scholarly knowledge in an open, online environment and address feedback. |- | style="vertical-align:top;" | Display initiative and drive | style="vertical-align:top;" | Produce an online book chapter about a novel motivation or emotion topic. |- | style="vertical-align:top;" | Up-to-date knowledge and skills | style="vertical-align:top;" | Utilise the most relevant psychological theory and research to address a practical question. |- | style="vertical-align:top;" | Solve problems via thinking | style="vertical-align:top;" | Use critical thinking to explain how psychological science can address real-world problems. |- | rowspan="3" style="vertical-align:top;" | '''Be a global citizen''' | style="vertical-align:top;" | Informed and balanced | style="vertical-align:top;" | Provide a balanced, critical chapter which is accessible to a lay audience. |- | style="vertical-align:top;" | Communicate diversely | style="vertical-align:top;" | Collaborate with peers to communicate knowledge openly with a global audience. |- | style="vertical-align:top;" | Creative use of technology | style="vertical-align:top;" | Learn how to collaborate using wiki technology. |- | rowspan="2" style="vertical-align:top;" | '''Be a lifelong learner''' | style="vertical-align:top;" | Engage in new ideas | style="vertical-align:top;" | Engage in a collaborative learning culture by incorporating feedback and suggestions. |- | style="vertical-align:top;" | Evaluate and adopt new technology | style="vertical-align:top;" | Experience project work in a collaborative, online editing environment. |} ==Instructions== The book chapter should communicate your understanding of the topic based on the best available psychological theory and research. Explain and apply the most relevant evidence in a clear, engaging, and accessible way. The aim is to demonstrate your ability to synthesise and critically evaluate psychological science in order to understand and respond to a specific motivation or emotion phenomenon. The following instructions should be used to guide the development of the book chapter. ===Theme=== * Chapters should fit the book theme which is "understanding and improving our motivational and emotional lives using psychological science" ===Audience=== * The target audience is a general (non-topic-expert) reader interested in personal growth and development based on knowledge in psychological science (theory and research). This is a [[w:science communication|science communication]] exercise. ===Wikiversity=== * Present the chapter as a single page on the [[Main Page|English Wikiversity]] website. A link to the chapter should appear in the [[Motivation and emotion/Book|table of contents]] along with the lead author's Wikiversity user name ===Topic=== * The title and sub-title must be approved by the [[Motivation and emotion/About/Staff|unit convener]] ===Collaboration and feedback=== * Chapters should be independently developed and written primarily by the lead author, but collaboration is strongly encouraged (e.g., by incorporating useful edits and feedback from others) * [[Motivation and emotion/Assessment/Using generative AI|Generative AI]] may be used with appropriate acknowledgement * Lead authors are encouraged to seek feedback about the chapter during the drafting process (e.g., start a {{Motivation and emotion/Canvas}} discussion thread<!-- (use the chapter title and subtitle in the subject line and include a clickable hyperlink to the chapter in the message)-->) * Feedback is usually best placed on the chapter's wiki discussion page * Feedback on the [[Motivation and emotion/Assessment/Topic|topic development]] (chapter plan) will be provided by the [[Motivation and emotion/About/Staff|unit convener]] ===Length (word count)=== {{Anchor|Wordcount}}{{Anchor|Word count}} * There is no minimum length * Maximum 4,000 words ** There is no additional 10% allowance ** Words beyond the maximum will not be considered for marking purposes ** If the chapter exceeds the maximum word count, see [[/Word count|these suggestions]] for strategies to reduce the length while retaining the key content. * What to count: ** Count everything from top to bottom of the editable page (in view mode, not edit mode) including the title, subtitle, headings, text, citations, tables, figures, references, see also, and external links ** Don't count menu text across the top and down the left, or categories at the bottom * How to count: ** Google Chrome extension: [https://chromewebstore.google.com/detail/word-counter/cbjddaobmdfhbfgdgjocbhklpmclcboe Word Counter]. This extension is probably the easiest reliable method for counting words on a Wikiversity page. However, UC recently started blocking this extension on UC devices. ** Website: Paste the URL into [https://hsuper.tools/web-page-word-counter Webpage Word Counter] (it overcounts by ~100 words because it includes menus etc.) ** Word processor: Cut and paste into a word processor (i.e., copy starting at title and finishing with the last external link) ===Submission=== * Submit the chapter URL (website address), your Wikiversity user name, and a PDF of the chapter via {{Motivation and emotion/Canvas}} ==Marking criteria== [[File:Balanced scales.svg|right|125px]] Book chapters will be marked against the following criteria. ===Overview (5%)=== * Scenario: Provide an engaging scenario or case study in a feature box, with an illustrative figure * Problem statement: Easy to read and understand outline of the key concepts and explanation of practical/real-world problem to be solved * Focus questions: Establish [[/Focus questions|focus questions]] which align with the sub-title and subsequent heading structure ===Theory (20%)=== * Clearly explain the theoretical framework for understanding the topic * Select the most relevant psychological theories/models that apply to the problem. Depending on the topic, this may involve focusing on a single theory or comparing and contrasting two or more theories. * Use at least the best dozen or so peer-reviewed theory references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Clearly explain and apply the theory(ies) * Include illustrative examples, such as case studies * Demonstrate a critical perspective ===Research (25%)=== * Clearly explain how key, peer-reviewed research findings apply to the problem * Use at least the best dozen or so peer-reviewed research references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Include relevant major reviews (such as systematic reviews and meta-analyses) * [[w:Critical thinking|Critical analyse]] the key research findings, including limitations and implications ===Integration (10%)=== * Integrate discussion of theory and review of relevant research * Use research to critically inform interpretation and application of the theory(ies) ===Conclusion (5%)=== * Clear and concise communication of key points and take-home messages * Aligned with the subtitle and focus questions, with implications for the [[Motivation and emotion/Book/Theme|book theme]] ===Style (20%)=== * Overall ** Present and illustrate the problem and knowledge in an interesting way, using a logical structure, clear layout, correct spelling and grammar, and [[APA style]] ** [[/Readability|Readable]] for a layperson interested in psychological science ** Address the [[#Theme|book theme]] by providing practical, academically sound, self-improvement information ** Address an international audience (i.e., avoid an overly local or national perspective) ** Use default wiki style for paragraph alignment, font colour, type, and size, and heading styles ** Use Australian spelling (e.g., hypothesise, behaviour, fulfilment) rather than American spelling (e.g., hypothesize, behavior, fulfillment) ** Correct grammar (e.g., see [[/Writing tips|writing tips]]) * Structure ** Use a logical heading structure that aligns with the focus questions ** Use [https://www.masterclass.com/articles/sentence-case-explained sentence casing] throughout, including for headings and sub-headings ** Use the default heading style (e.g., do not add italics and/or bold) ** Sub-headings are optional *** Avoid having sections with a single sub-heading — each section should contain 0 or 2+ sub-headings. *** If sub-headings are used, provides at least 1 introductory paragraph before branching into sub-sections. * Sentences ** [[w:Narration#Narrative point of view|Narrative point of view]][https://www.grammarly.com/blog/first-second-and-third-person/]: In the main text, use [[w:Narration#Third-person|3rd person perspective]] (e.g., "it", "they"). Where [[w:Aside|aside]]s are used, such as examples, case studies, and feature boxes, [[w:First-person narrative|1st person perspective]] (e.g., "I" and "we") and/or [[w:Narration#Second-person|2nd person perspective]] (e.g., "you") can work well. * Paragraphs ** A well-constructed paragraph is generally 3 to 5 sentences (opening sentence, body sentences, and a concluding/linking sentence). Avoid one-sentence paragraphs and overly long paragraphs. ** Paragraphs flow logically * Use APA style (as much as reasonably possible), paying particular attention to: ** citations ** references (especially capitalisation, italicisation, and providing hyperlinked dois) ** table and figure captions ** quotes (include page numbers) * Citations ** Claims need citations using APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style throughout the chapter — don't mix and match. For most psychology students, APA style will be the choice. ** Maximum of 3 citations per point (i.e., avoid 4 or more citations together). * References ** List all cited academic references in APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style. ** Non-academic sources are not used in references. They can be included in the external links section. ===Learning features (5%)=== * Embed interactive learning features such as scenarios/case studies/examples, feature boxes, figures, quizzes, links to relevant Wikipedia and Wikipedia pages, as well as links to key resources via the "See also" and "External links" sections * Case studies ** Include 1 or more examples, scenarios, or case studies ** They can be true (if so, include citations) or fictional ** Use these examples to enhance understanding of theory, research, focus questions, and/or take-home messages ** Present in a feature box and include a figure ** Consider using a "progressive case study" (i.e., a case study presented in separate parts which describe, for example, the problem, attempt at change, and resolution/outcomes). ** Examples of chapters which make effective use of case studies: *** [[Motivation and emotion/Book/2019/Emotional abuse|emotional abuse]] (2019) *** [[Motivation and emotion/Book/2019/Food and fear|food and fear]] (2019) *** [[Motivation and emotion/Book/2019/Opioid system and human emotion|opioid system and human emotion]] (2019) *** [[Motivation and emotion/Book/2019/Social support and emotion|social support and emotion]] (2019) * [[Motivation and emotion/Wikiversity/Feature box|Feature boxes]] ** Use to highlight key information, but avoid overuse ** There are various ways of creating coloured boxes, but the [[Template:RoundBoxTop|RoundBox]] template is a good option. * [[Motivation and emotion/Wikiversity/Figures|Figures]] ** Include relevant, accompanying figures (e.g., photos, drawings, diagrams) to facilitate readers' understanding of the concepts ** Figures are accompanied by explanatory captions and be cited at least once in the main text ** For more information, see [[Motivation and emotion/Assessment/Chapter/Figures|How to use figures]]). * [[Help:Links|Links]] ** In-text (embedded) links: Key words and concepts are [[Making links|linked]] to Wikipedia articles and/or related book chapters. Provide in-text wiki links the ''first time'' that key concepts are mentioned. For example: *** [[w:Emotion|emotion]] involves physiological, subjective feeling, motivational, and socially expressive aspects. The syntax for creating this link is <nowiki>[[w:Emotion|emotion]]</nowiki>). It is also possible to link to a section on this same page e.g., &lt;nowiki&gt;[[#Overview|Overview]]&lt;nowiki&gt; will link to the Overview section. *** [[Motivation and emotion/Book/2021/Fitspiration and body image|This chapter]] provides an excellent example of embedded links to Wikiversity pages. ** See also *** Provide interwiki links to key related Wikiversity book chapters and/or Wikipedia articles *** Include source in parentheses ** External links *** Provide at least three links to high quality, relevant external resources *** Include author and/or source in parentheses ** Published academic sources belong in References * [[Motivation and emotion/Wikiversity/Tables|Tables]] ** Use accompanying tables to help organise information and communicate concepts to readers ** Tables are accompanied by explanatory APA style captions and are cited in the body text * [[Help:Quiz|Quizzes]] ** Quiz questions or reflection questions encourage reader engagement ** Focus on core concepts (esp. take-home messages) rather than trivia ** Consider incorporating throughout the chapter {{anchor|Socialcontribution}} {{anchor|Social contribution}} ===Social contribution (10%)=== * '''Actions''': Logged contributions which enhance the quality of other book chapters. Useful actions include: ** '''Edits''': Direct edits which improve past or current chapters (e.g., fix errors, enhance clarity) or flag potential improvements by adding [[Template:Clarification templates|clarification templates]]. [[/Search for chapters to improve|Search for chapters to improve]]. ** '''Comments''': Feedback provided on book chapter [[Help:Talk page|talk page]]s ** '''Media uploads''': Upload free-to-use educational images to [[commons:|Wikimedia Commons]] ** '''{{Motivation and emotion/Canvas}} discussion posts''' * '''Evidence''': ** Provide a [[mw:Help:Lists|numbered list]] with summaries of contributions on your [[Help:User page|Wikiversity user page]], and '''direct links''' that show each change or contribution.<!-- To receive credit, contributions must be publicly logged (i.e., log in to Wikiversity so that the edit is recorded with your user name and time-stamp). Summarise each edit on your user page (in a section called "Social contributions") --> ** More info: [[/Summarising social contributions|summarising social contributions]] * '''Marking''' ** Marking of social contributions will be based on a combination of: *** '''Quantity''': **** Breadth: number of chapters contributed to **** Channels: range of communication channels used *** '''Quality''': **** Depth/extent/thoroughness **** Insightfulness **** Practical value *** '''Timeliness''' — there is generally: **** Greater value in earlier contributions **** Lesser value in last-minute contributions ** Marks will be allocated to each clearly evidenced contribution as follows: *** Minor <= 0.25 *** Moderate 0.50 *** Major 1.00 *** Very significant > 1.00 * '''Bonus marks''' ** Up to 5 bonus marks (out of 100 for the book chapter) will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level. ** Approximately 5% of students receive social contribution bonus marks. ** This could include extensive copyediting of multiple chapters and/or regular feedback or support on multiple chapter discussion pages. It may also involve substantial activity on the UCLearn discussion forum. ==Marking rubric== {{Notice|1=[https://docs.google.com/document/d/1yQd1-IekznJNLwhef-yEBaxKtRR6dAVESWXoTa-ti3c/edit?usp=sharing Marking rubric]}} ==Examples== Examples of high quality [[Motivation and emotion/Book|motivation and emotion book chapters]]: * [[Motivation and emotion/Book/2025/AI use, cognitive load, and motivation|AI use, cognitive load, and motivation]] - How does generative AI reduce cognitive effort, and what are the motivational consequences? (2025) * [[Motivation and emotion/Book/2025/Autonomy and intrinsic motivation in self-determination theory|Autonomy and intrinsic motivation in self-determination theory]]: How does autonomy influence intrinsic motivation according to SDT? (2025) * [[Motivation and emotion/Book/2022/Disappointment|Disappointment]]: What is disappointment, what causes it, and how can it be managed? (2022) * [[Motivation and emotion/Book/2016/Illicit drug taking at music festivals|Illicit drug taking at music festivals]]: What motivates young people to take illicit drugs at music festivals? (2016) * [[Motivation and emotion/Book/2019/Organisational change motivation|Organisational change motivation]]: How can leaders build a culture of agility, adaptability, and resilience to deal with a constantly changing workplace? (2019) * [[Motivation and emotion/Book/2019/Phobias|Phobias]]: What are phobias and how can they be dealt with? (2019) * [[Motivation and emotion/Book/2025/Transactive goal dynamics theory and motivation|Transactive goal dynamics theory and motivation]]: What is transactive goal dynamics theory and how does it impact motivation? (2025) Note that as of 2025, chapters no longer include multimedia presentations. For more examples, see the {{Motivation and emotion/Book/High}}s in the [[Motivation and emotion/Book|lists of previous book chapters]]<!-- and the [[:Category:Motivation and emotion/Book/2022/Top|top chapters of 2022]] -->. ==Licensing== Contributions to Wikiversity are made under a [http://creativecommons.org/licenses/by-sa/4.0/ Creative Commons 4.0 Share-alike] (CC-BY-SA 4.0) license which is irrevocable. This license gives permission for others to edit and re-use, with appropriate acknowledgement. For more information, see the [[wmf:Terms of use|Wikimedia Foundation's Terms of use]]. If you do not wish to contribute your work under this license, discuss [[Motivation and emotion/Assessment/Alternative|alternative assessment options]] with the unit convener. ==See also== * [[/FAQ/]] * [[Motivation and emotion/Book|Previous chapters]] * Marking and feedback ** [[Motivation and emotion/Assessment/Chapter/Feedback|General feedback]] ** [[Template:MEBF|Feedback template]] ** [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing Marking rubric] * [[#Socialcontribution|Social contributions]] ** [[/Search for chapters to improve/]] ** [[/Summarising social contributions/]] * [[Motivation and emotion/Tutorials|Tutorials]] <!-- ** [[Motivation and emotion/Tutorials/Topic selection|Tutorial 01: Topic selection]] --> ** [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2: Wiki editing]] ** [[Motivation and emotion/Tutorials/Functionalist theory and self-tracking#Google Scholar|Tutorial 5: Google Scholar]] ** [[Motivation and emotion/Tutorials/Measuring emotion#Topic development feedback|Tutorial 8: Topic development feedback]] * Wikiversity ** [[/Feature boxes/]] ** [[/Figures/]] ** [[How to find free-to-use images|Find free images]] ** [[/Tables/]] * [[/Writing tips/]] ** [[/How to handle a lack of information/|Handling a lack of information]] ** [[/Readability|Readability]] ** [[Motivation and emotion/Assessment/Using generative AI|Using generative AI]] ** [[/Word count|Word count]] {{Motivation and emotion/Assessment/Navigation}} [[Category:Motivation and emotion/Assessment/Chapter| ]] [[Category:Motivation and emotion guidelines]] ts5ueofznvwwszpdq2v9mv6vw7rbryu 2835400 2835399 2026-10-01T22:32:38Z Jtneill 10242 /* Length (word count) */ 2835400 wikitext text/x-wiki {{title|Book chapter — Guidelines}} <div style="text-align: center;">''Collaborative online book chapter authoring'' <!-- ---------------------------------- ---> <!-- Count down --> <!-- ---------------------------------- ---><!-- {{countdown |year = 2026 |month = 10 |day = 12 |hour = 0 |event = this assessment is due }} --><!-- {{Motivation and emotion/Assessment/In development}} --> {{/Contents/}}</div> {{TOCright}} ==Overview== * Weight: 50% * Due {{/Due}} * Tasks ** Author an online [[Motivation and emotion/Book|book chapter]] (up to 4,000 words) that explains key psychological theory and research about a unique, specific motivation or emotion topic. ** Develop the chapter by building on the [[Motivation and emotion/Assessment/Topic|topic development]] plan and addressing feedback. ** Contribute to the development of other book chapters (social contribution). * Follow the [[#Instructions|instructions]] and address the [[#Marking criteria|marking criteria]]. ==Purpose== The purpose of the book chapter is to explain and critically evaluate what psychological science says about a specific motivation or emotion topic, and to demonstrate how this knowledge can be applied to understanding and improving human behaviour in everyday life. ==Marking and feedback== * Submissions will be marked according to the [[#Marking criteria|marking criteria]] and [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing marking rubric]. * Marks will be provided via {{Motivation and emotion/Canvas}} when the university releases unit results (see [https://www.canberra.edu.au/about-uc/key-dates/ Key dates]). * Up to 5 bonus marks will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level (see [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60 rubric]). * Written feedback about how well the chapter addresses the marking criteria will be available via the topic's Wikiversity discussion page. * Follow up with the [[Motivation and emotion/About/Staff|unit convener]] if you have any questions. ==Extensions and late submissions== * Apply for extension using the unit's online Extension Application Form (see {{Motivation and emotion/Canvas}}) with appropriate documentary evidence. * Submissions will be accepted up to 3 days late (-10% per day). * If you don't submit this assessment it is unlikely that you will pass the unit. ==Learning outcomes== How the unit's [[Motivation and emotion/About/Learning outcomes|learning outcomes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto; vertical-align:top;" |- | style="width:40%;" | '''Learning outcome''' | style="width:60%;" | '''Assessment task''' |- | style="vertical-align:top;" | Integrate theories and current research towards explaining the role of motivation and emotions in human behaviour. | style="vertical-align:top;" | Use the most relevant theories and peer-reviewed research to explain a specific motivation or emotion topic. |- | style="vertical-align:top;" | Critically apply knowledge of motivation or emotion to an indepth understanding of a specific topic in this field. | style="vertical-align:top;" | Explain how psychological science can be applied to a specific motivation or emotion topic. Use figures, examples, and/or other interactive learning features to illustrate how this knowledge can apply to understanding human behaviour in everyday life. |} ==Graduate attributes== How the unit's [[Motivation and emotion/About/Graduate attributes|graduate attributes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto;" |- ! style="width:20%;" | Category ! style="width:20%;" | Graduate attribute ! style="width:60%;" | Assessment task |- | rowspan="4" style="vertical-align:top;" | '''Be professional''' | style="vertical-align:top;" | Communicate effectively | style="vertical-align:top;" | Review scholarly knowledge in an open, online environment and address feedback. |- | style="vertical-align:top;" | Display initiative and drive | style="vertical-align:top;" | Produce an online book chapter about a novel motivation or emotion topic. |- | style="vertical-align:top;" | Up-to-date knowledge and skills | style="vertical-align:top;" | Utilise the most relevant psychological theory and research to address a practical question. |- | style="vertical-align:top;" | Solve problems via thinking | style="vertical-align:top;" | Use critical thinking to explain how psychological science can address real-world problems. |- | rowspan="3" style="vertical-align:top;" | '''Be a global citizen''' | style="vertical-align:top;" | Informed and balanced | style="vertical-align:top;" | Provide a balanced, critical chapter which is accessible to a lay audience. |- | style="vertical-align:top;" | Communicate diversely | style="vertical-align:top;" | Collaborate with peers to communicate knowledge openly with a global audience. |- | style="vertical-align:top;" | Creative use of technology | style="vertical-align:top;" | Learn how to collaborate using wiki technology. |- | rowspan="2" style="vertical-align:top;" | '''Be a lifelong learner''' | style="vertical-align:top;" | Engage in new ideas | style="vertical-align:top;" | Engage in a collaborative learning culture by incorporating feedback and suggestions. |- | style="vertical-align:top;" | Evaluate and adopt new technology | style="vertical-align:top;" | Experience project work in a collaborative, online editing environment. |} ==Instructions== The book chapter should communicate your understanding of the topic based on the best available psychological theory and research. Explain and apply the most relevant evidence in a clear, engaging, and accessible way. The aim is to demonstrate your ability to synthesise and critically evaluate psychological science in order to understand and respond to a specific motivation or emotion phenomenon. The following instructions should be used to guide the development of the book chapter. ===Theme=== * Chapters should fit the book theme which is "understanding and improving our motivational and emotional lives using psychological science" ===Audience=== * The target audience is a general (non-topic-expert) reader interested in personal growth and development based on knowledge in psychological science (theory and research). This is a [[w:science communication|science communication]] exercise. ===Wikiversity=== * Present the chapter as a single page on the [[Main Page|English Wikiversity]] website. A link to the chapter should appear in the [[Motivation and emotion/Book|table of contents]] along with the lead author's Wikiversity user name ===Topic=== * The title and sub-title must be approved by the [[Motivation and emotion/About/Staff|unit convener]] ===Collaboration and feedback=== * Chapters should be independently developed and written primarily by the lead author, but collaboration is strongly encouraged (e.g., by incorporating useful edits and feedback from others) * [[Motivation and emotion/Assessment/Using generative AI|Generative AI]] may be used with appropriate acknowledgement * Lead authors are encouraged to seek feedback about the chapter during the drafting process (e.g., start a {{Motivation and emotion/Canvas}} discussion thread<!-- (use the chapter title and subtitle in the subject line and include a clickable hyperlink to the chapter in the message)-->) * Feedback is usually best placed on the chapter's wiki discussion page * Feedback on the [[Motivation and emotion/Assessment/Topic|topic development]] (chapter plan) will be provided by the [[Motivation and emotion/About/Staff|unit convener]] ===Length (word count)=== {{Anchor|Wordcount}}{{Anchor|Word count}} * There is no minimum length * Maximum 4,000 words ** There is no additional 10% allowance ** Words beyond the maximum will not be considered for marking purposes ** If the chapter exceeds the maximum word count, see [[/Word count|these suggestions]] for strategies to reduce the length while retaining the key content * What to count: ** Count everything from top to bottom of the editable page (in view mode, not edit mode) including the title, subtitle, headings, text, citations, tables, figures, references, see also, and external links ** Don't count menu text across the top and down the left, or categories at the bottom * How to count: ** Google Chrome extension: [https://chromewebstore.google.com/detail/word-counter/cbjddaobmdfhbfgdgjocbhklpmclcboe Word Counter]. This extension is probably the easiest reliable method for counting words on a Wikiversity page. However, UC recently started blocking this extension on UC devices. ** Website: Paste the URL into [https://hsuper.tools/web-page-word-counter Webpage Word Counter] (it overcounts by ~100 words because it includes menus etc.) ** Word processor: Cut and paste into a word processor (i.e., copy starting at title and finishing with the last external link) ===Submission=== * Submit the chapter URL (website address), your Wikiversity user name, and a PDF of the chapter via {{Motivation and emotion/Canvas}} ==Marking criteria== [[File:Balanced scales.svg|right|125px]] Book chapters will be marked against the following criteria. ===Overview (5%)=== * Scenario: Provide an engaging scenario or case study in a feature box, with an illustrative figure * Problem statement: Easy to read and understand outline of the key concepts and explanation of practical/real-world problem to be solved * Focus questions: Establish [[/Focus questions|focus questions]] which align with the sub-title and subsequent heading structure ===Theory (20%)=== * Clearly explain the theoretical framework for understanding the topic * Select the most relevant psychological theories/models that apply to the problem. Depending on the topic, this may involve focusing on a single theory or comparing and contrasting two or more theories. * Use at least the best dozen or so peer-reviewed theory references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Clearly explain and apply the theory(ies) * Include illustrative examples, such as case studies * Demonstrate a critical perspective ===Research (25%)=== * Clearly explain how key, peer-reviewed research findings apply to the problem * Use at least the best dozen or so peer-reviewed research references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Include relevant major reviews (such as systematic reviews and meta-analyses) * [[w:Critical thinking|Critical analyse]] the key research findings, including limitations and implications ===Integration (10%)=== * Integrate discussion of theory and review of relevant research * Use research to critically inform interpretation and application of the theory(ies) ===Conclusion (5%)=== * Clear and concise communication of key points and take-home messages * Aligned with the subtitle and focus questions, with implications for the [[Motivation and emotion/Book/Theme|book theme]] ===Style (20%)=== * Overall ** Present and illustrate the problem and knowledge in an interesting way, using a logical structure, clear layout, correct spelling and grammar, and [[APA style]] ** [[/Readability|Readable]] for a layperson interested in psychological science ** Address the [[#Theme|book theme]] by providing practical, academically sound, self-improvement information ** Address an international audience (i.e., avoid an overly local or national perspective) ** Use default wiki style for paragraph alignment, font colour, type, and size, and heading styles ** Use Australian spelling (e.g., hypothesise, behaviour, fulfilment) rather than American spelling (e.g., hypothesize, behavior, fulfillment) ** Correct grammar (e.g., see [[/Writing tips|writing tips]]) * Structure ** Use a logical heading structure that aligns with the focus questions ** Use [https://www.masterclass.com/articles/sentence-case-explained sentence casing] throughout, including for headings and sub-headings ** Use the default heading style (e.g., do not add italics and/or bold) ** Sub-headings are optional *** Avoid having sections with a single sub-heading — each section should contain 0 or 2+ sub-headings. *** If sub-headings are used, provides at least 1 introductory paragraph before branching into sub-sections. * Sentences ** [[w:Narration#Narrative point of view|Narrative point of view]][https://www.grammarly.com/blog/first-second-and-third-person/]: In the main text, use [[w:Narration#Third-person|3rd person perspective]] (e.g., "it", "they"). Where [[w:Aside|aside]]s are used, such as examples, case studies, and feature boxes, [[w:First-person narrative|1st person perspective]] (e.g., "I" and "we") and/or [[w:Narration#Second-person|2nd person perspective]] (e.g., "you") can work well. * Paragraphs ** A well-constructed paragraph is generally 3 to 5 sentences (opening sentence, body sentences, and a concluding/linking sentence). Avoid one-sentence paragraphs and overly long paragraphs. ** Paragraphs flow logically * Use APA style (as much as reasonably possible), paying particular attention to: ** citations ** references (especially capitalisation, italicisation, and providing hyperlinked dois) ** table and figure captions ** quotes (include page numbers) * Citations ** Claims need citations using APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style throughout the chapter — don't mix and match. For most psychology students, APA style will be the choice. ** Maximum of 3 citations per point (i.e., avoid 4 or more citations together). * References ** List all cited academic references in APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style. ** Non-academic sources are not used in references. They can be included in the external links section. ===Learning features (5%)=== * Embed interactive learning features such as scenarios/case studies/examples, feature boxes, figures, quizzes, links to relevant Wikipedia and Wikipedia pages, as well as links to key resources via the "See also" and "External links" sections * Case studies ** Include 1 or more examples, scenarios, or case studies ** They can be true (if so, include citations) or fictional ** Use these examples to enhance understanding of theory, research, focus questions, and/or take-home messages ** Present in a feature box and include a figure ** Consider using a "progressive case study" (i.e., a case study presented in separate parts which describe, for example, the problem, attempt at change, and resolution/outcomes). ** Examples of chapters which make effective use of case studies: *** [[Motivation and emotion/Book/2019/Emotional abuse|emotional abuse]] (2019) *** [[Motivation and emotion/Book/2019/Food and fear|food and fear]] (2019) *** [[Motivation and emotion/Book/2019/Opioid system and human emotion|opioid system and human emotion]] (2019) *** [[Motivation and emotion/Book/2019/Social support and emotion|social support and emotion]] (2019) * [[Motivation and emotion/Wikiversity/Feature box|Feature boxes]] ** Use to highlight key information, but avoid overuse ** There are various ways of creating coloured boxes, but the [[Template:RoundBoxTop|RoundBox]] template is a good option. * [[Motivation and emotion/Wikiversity/Figures|Figures]] ** Include relevant, accompanying figures (e.g., photos, drawings, diagrams) to facilitate readers' understanding of the concepts ** Figures are accompanied by explanatory captions and be cited at least once in the main text ** For more information, see [[Motivation and emotion/Assessment/Chapter/Figures|How to use figures]]). * [[Help:Links|Links]] ** In-text (embedded) links: Key words and concepts are [[Making links|linked]] to Wikipedia articles and/or related book chapters. Provide in-text wiki links the ''first time'' that key concepts are mentioned. For example: *** [[w:Emotion|emotion]] involves physiological, subjective feeling, motivational, and socially expressive aspects. The syntax for creating this link is <nowiki>[[w:Emotion|emotion]]</nowiki>). It is also possible to link to a section on this same page e.g., &lt;nowiki&gt;[[#Overview|Overview]]&lt;nowiki&gt; will link to the Overview section. *** [[Motivation and emotion/Book/2021/Fitspiration and body image|This chapter]] provides an excellent example of embedded links to Wikiversity pages. ** See also *** Provide interwiki links to key related Wikiversity book chapters and/or Wikipedia articles *** Include source in parentheses ** External links *** Provide at least three links to high quality, relevant external resources *** Include author and/or source in parentheses ** Published academic sources belong in References * [[Motivation and emotion/Wikiversity/Tables|Tables]] ** Use accompanying tables to help organise information and communicate concepts to readers ** Tables are accompanied by explanatory APA style captions and are cited in the body text * [[Help:Quiz|Quizzes]] ** Quiz questions or reflection questions encourage reader engagement ** Focus on core concepts (esp. take-home messages) rather than trivia ** Consider incorporating throughout the chapter {{anchor|Socialcontribution}} {{anchor|Social contribution}} ===Social contribution (10%)=== * '''Actions''': Logged contributions which enhance the quality of other book chapters. Useful actions include: ** '''Edits''': Direct edits which improve past or current chapters (e.g., fix errors, enhance clarity) or flag potential improvements by adding [[Template:Clarification templates|clarification templates]]. [[/Search for chapters to improve|Search for chapters to improve]]. ** '''Comments''': Feedback provided on book chapter [[Help:Talk page|talk page]]s ** '''Media uploads''': Upload free-to-use educational images to [[commons:|Wikimedia Commons]] ** '''{{Motivation and emotion/Canvas}} discussion posts''' * '''Evidence''': ** Provide a [[mw:Help:Lists|numbered list]] with summaries of contributions on your [[Help:User page|Wikiversity user page]], and '''direct links''' that show each change or contribution.<!-- To receive credit, contributions must be publicly logged (i.e., log in to Wikiversity so that the edit is recorded with your user name and time-stamp). Summarise each edit on your user page (in a section called "Social contributions") --> ** More info: [[/Summarising social contributions|summarising social contributions]] * '''Marking''' ** Marking of social contributions will be based on a combination of: *** '''Quantity''': **** Breadth: number of chapters contributed to **** Channels: range of communication channels used *** '''Quality''': **** Depth/extent/thoroughness **** Insightfulness **** Practical value *** '''Timeliness''' — there is generally: **** Greater value in earlier contributions **** Lesser value in last-minute contributions ** Marks will be allocated to each clearly evidenced contribution as follows: *** Minor <= 0.25 *** Moderate 0.50 *** Major 1.00 *** Very significant > 1.00 * '''Bonus marks''' ** Up to 5 bonus marks (out of 100 for the book chapter) will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level. ** Approximately 5% of students receive social contribution bonus marks. ** This could include extensive copyediting of multiple chapters and/or regular feedback or support on multiple chapter discussion pages. It may also involve substantial activity on the UCLearn discussion forum. ==Marking rubric== {{Notice|1=[https://docs.google.com/document/d/1yQd1-IekznJNLwhef-yEBaxKtRR6dAVESWXoTa-ti3c/edit?usp=sharing Marking rubric]}} ==Examples== Examples of high quality [[Motivation and emotion/Book|motivation and emotion book chapters]]: * [[Motivation and emotion/Book/2025/AI use, cognitive load, and motivation|AI use, cognitive load, and motivation]] - How does generative AI reduce cognitive effort, and what are the motivational consequences? (2025) * [[Motivation and emotion/Book/2025/Autonomy and intrinsic motivation in self-determination theory|Autonomy and intrinsic motivation in self-determination theory]]: How does autonomy influence intrinsic motivation according to SDT? (2025) * [[Motivation and emotion/Book/2022/Disappointment|Disappointment]]: What is disappointment, what causes it, and how can it be managed? (2022) * [[Motivation and emotion/Book/2016/Illicit drug taking at music festivals|Illicit drug taking at music festivals]]: What motivates young people to take illicit drugs at music festivals? (2016) * [[Motivation and emotion/Book/2019/Organisational change motivation|Organisational change motivation]]: How can leaders build a culture of agility, adaptability, and resilience to deal with a constantly changing workplace? (2019) * [[Motivation and emotion/Book/2019/Phobias|Phobias]]: What are phobias and how can they be dealt with? (2019) * [[Motivation and emotion/Book/2025/Transactive goal dynamics theory and motivation|Transactive goal dynamics theory and motivation]]: What is transactive goal dynamics theory and how does it impact motivation? (2025) Note that as of 2025, chapters no longer include multimedia presentations. For more examples, see the {{Motivation and emotion/Book/High}}s in the [[Motivation and emotion/Book|lists of previous book chapters]]<!-- and the [[:Category:Motivation and emotion/Book/2022/Top|top chapters of 2022]] -->. ==Licensing== Contributions to Wikiversity are made under a [http://creativecommons.org/licenses/by-sa/4.0/ Creative Commons 4.0 Share-alike] (CC-BY-SA 4.0) license which is irrevocable. This license gives permission for others to edit and re-use, with appropriate acknowledgement. For more information, see the [[wmf:Terms of use|Wikimedia Foundation's Terms of use]]. If you do not wish to contribute your work under this license, discuss [[Motivation and emotion/Assessment/Alternative|alternative assessment options]] with the unit convener. ==See also== * [[/FAQ/]] * [[Motivation and emotion/Book|Previous chapters]] * Marking and feedback ** [[Motivation and emotion/Assessment/Chapter/Feedback|General feedback]] ** [[Template:MEBF|Feedback template]] ** [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing Marking rubric] * [[#Socialcontribution|Social contributions]] ** [[/Search for chapters to improve/]] ** [[/Summarising social contributions/]] * [[Motivation and emotion/Tutorials|Tutorials]] <!-- ** [[Motivation and emotion/Tutorials/Topic selection|Tutorial 01: Topic selection]] --> ** [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2: Wiki editing]] ** [[Motivation and emotion/Tutorials/Functionalist theory and self-tracking#Google Scholar|Tutorial 5: Google Scholar]] ** [[Motivation and emotion/Tutorials/Measuring emotion#Topic development feedback|Tutorial 8: Topic development feedback]] * Wikiversity ** [[/Feature boxes/]] ** [[/Figures/]] ** [[How to find free-to-use images|Find free images]] ** [[/Tables/]] * [[/Writing tips/]] ** [[/How to handle a lack of information/|Handling a lack of information]] ** [[/Readability|Readability]] ** [[Motivation and emotion/Assessment/Using generative AI|Using generative AI]] ** [[/Word count|Word count]] {{Motivation and emotion/Assessment/Navigation}} [[Category:Motivation and emotion/Assessment/Chapter| ]] [[Category:Motivation and emotion guidelines]] rfbpfi22si9tjkicxgee8qpfxoxwogg 2835463 2835400 2026-10-02T05:35:25Z Jtneill 10242 /* Length (word count) */ ** '''Wikiversity search:''' Copy the page name text which appears at the top of the Wikiversity page (e.g., ''Motivation and emotion/Book/2026/Self-concept and motivation''). Paste this text into the Wikiversity search bar at the top of the page and select the second option, '''Search for pages containing [your title]'''. The first result should be your book chapter. The search result provides information about the chapter, including its word count. 2835463 wikitext text/x-wiki {{title|Book chapter — Guidelines}} <div style="text-align: center;">''Collaborative online book chapter authoring'' <!-- ---------------------------------- ---> <!-- Count down --> <!-- ---------------------------------- ---><!-- {{countdown |year = 2026 |month = 10 |day = 12 |hour = 0 |event = this assessment is due }} --><!-- {{Motivation and emotion/Assessment/In development}} --> {{/Contents/}}</div> {{TOCright}} ==Overview== * Weight: 50% * Due {{/Due}} * Tasks ** Author an online [[Motivation and emotion/Book|book chapter]] (up to 4,000 words) that explains key psychological theory and research about a unique, specific motivation or emotion topic. ** Develop the chapter by building on the [[Motivation and emotion/Assessment/Topic|topic development]] plan and addressing feedback. ** Contribute to the development of other book chapters (social contribution). * Follow the [[#Instructions|instructions]] and address the [[#Marking criteria|marking criteria]]. ==Purpose== The purpose of the book chapter is to explain and critically evaluate what psychological science says about a specific motivation or emotion topic, and to demonstrate how this knowledge can be applied to understanding and improving human behaviour in everyday life. ==Marking and feedback== * Submissions will be marked according to the [[#Marking criteria|marking criteria]] and [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing marking rubric]. * Marks will be provided via {{Motivation and emotion/Canvas}} when the university releases unit results (see [https://www.canberra.edu.au/about-uc/key-dates/ Key dates]). * Up to 5 bonus marks will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level (see [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60 rubric]). * Written feedback about how well the chapter addresses the marking criteria will be available via the topic's Wikiversity discussion page. * Follow up with the [[Motivation and emotion/About/Staff|unit convener]] if you have any questions. ==Extensions and late submissions== * Apply for extension using the unit's online Extension Application Form (see {{Motivation and emotion/Canvas}}) with appropriate documentary evidence. * Submissions will be accepted up to 3 days late (-10% per day). * If you don't submit this assessment it is unlikely that you will pass the unit. ==Learning outcomes== How the unit's [[Motivation and emotion/About/Learning outcomes|learning outcomes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto; vertical-align:top;" |- | style="width:40%;" | '''Learning outcome''' | style="width:60%;" | '''Assessment task''' |- | style="vertical-align:top;" | Integrate theories and current research towards explaining the role of motivation and emotions in human behaviour. | style="vertical-align:top;" | Use the most relevant theories and peer-reviewed research to explain a specific motivation or emotion topic. |- | style="vertical-align:top;" | Critically apply knowledge of motivation or emotion to an indepth understanding of a specific topic in this field. | style="vertical-align:top;" | Explain how psychological science can be applied to a specific motivation or emotion topic. Use figures, examples, and/or other interactive learning features to illustrate how this knowledge can apply to understanding human behaviour in everyday life. |} ==Graduate attributes== How the unit's [[Motivation and emotion/About/Graduate attributes|graduate attributes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto;" |- ! style="width:20%;" | Category ! style="width:20%;" | Graduate attribute ! style="width:60%;" | Assessment task |- | rowspan="4" style="vertical-align:top;" | '''Be professional''' | style="vertical-align:top;" | Communicate effectively | style="vertical-align:top;" | Review scholarly knowledge in an open, online environment and address feedback. |- | style="vertical-align:top;" | Display initiative and drive | style="vertical-align:top;" | Produce an online book chapter about a novel motivation or emotion topic. |- | style="vertical-align:top;" | Up-to-date knowledge and skills | style="vertical-align:top;" | Utilise the most relevant psychological theory and research to address a practical question. |- | style="vertical-align:top;" | Solve problems via thinking | style="vertical-align:top;" | Use critical thinking to explain how psychological science can address real-world problems. |- | rowspan="3" style="vertical-align:top;" | '''Be a global citizen''' | style="vertical-align:top;" | Informed and balanced | style="vertical-align:top;" | Provide a balanced, critical chapter which is accessible to a lay audience. |- | style="vertical-align:top;" | Communicate diversely | style="vertical-align:top;" | Collaborate with peers to communicate knowledge openly with a global audience. |- | style="vertical-align:top;" | Creative use of technology | style="vertical-align:top;" | Learn how to collaborate using wiki technology. |- | rowspan="2" style="vertical-align:top;" | '''Be a lifelong learner''' | style="vertical-align:top;" | Engage in new ideas | style="vertical-align:top;" | Engage in a collaborative learning culture by incorporating feedback and suggestions. |- | style="vertical-align:top;" | Evaluate and adopt new technology | style="vertical-align:top;" | Experience project work in a collaborative, online editing environment. |} ==Instructions== The book chapter should communicate your understanding of the topic based on the best available psychological theory and research. Explain and apply the most relevant evidence in a clear, engaging, and accessible way. The aim is to demonstrate your ability to synthesise and critically evaluate psychological science in order to understand and respond to a specific motivation or emotion phenomenon. The following instructions should be used to guide the development of the book chapter. ===Theme=== * Chapters should fit the book theme which is "understanding and improving our motivational and emotional lives using psychological science" ===Audience=== * The target audience is a general (non-topic-expert) reader interested in personal growth and development based on knowledge in psychological science (theory and research). This is a [[w:science communication|science communication]] exercise. ===Wikiversity=== * Present the chapter as a single page on the [[Main Page|English Wikiversity]] website. A link to the chapter should appear in the [[Motivation and emotion/Book|table of contents]] along with the lead author's Wikiversity user name ===Topic=== * The title and sub-title must be approved by the [[Motivation and emotion/About/Staff|unit convener]] ===Collaboration and feedback=== * Chapters should be independently developed and written primarily by the lead author, but collaboration is strongly encouraged (e.g., by incorporating useful edits and feedback from others) * [[Motivation and emotion/Assessment/Using generative AI|Generative AI]] may be used with appropriate acknowledgement * Lead authors are encouraged to seek feedback about the chapter during the drafting process (e.g., start a {{Motivation and emotion/Canvas}} discussion thread<!-- (use the chapter title and subtitle in the subject line and include a clickable hyperlink to the chapter in the message)-->) * Feedback is usually best placed on the chapter's wiki discussion page * Feedback on the [[Motivation and emotion/Assessment/Topic|topic development]] (chapter plan) will be provided by the [[Motivation and emotion/About/Staff|unit convener]] ===Length (word count)=== {{Anchor|Wordcount}}{{Anchor|Word count}} * There is no minimum length * Maximum 4,000 words ** There is no additional 10% allowance ** Words beyond the maximum will not be considered for marking purposes ** If the chapter exceeds the maximum word count, see [[/Word count|these suggestions]] for strategies to reduce the length while retaining the key content * What to count: ** Count everything from top to bottom of the editable page (in view mode, not edit mode) including the title, subtitle, headings, text, citations, tables, figures, references, see also, and external links ** Don't count menu text across the top and down the left, or categories at the bottom * How to count: ** '''Wikiversity search:''' Copy the page name text which appears at the top of the Wikiversity page (e.g., ''Motivation and emotion/Book/2026/Self-concept and motivation''). Paste this text into the Wikiversity search bar at the top of the page and select the second option, '''Search for pages containing [your title]'''. The first result should be your book chapter. The search result provides information about the chapter, including its word count. ** '''Google Chrome extension:''' [https://chromewebstore.google.com/detail/word-counter/cbjddaobmdfhbfgdgjocbhklpmclcboe Word Counter]. This extension is an easy, reliable method for counting words on a Wikiversity page. '''Cons:''' UC recently blocked this extension on UC devices. ** '''Website:''' Paste the URL into [https://hsuper.tools/web-page-word-counter Webpage Word Counter]. '''Cons:''' Overcounts by approximately 100 words because it includes top and side menus and other page elements. ** '''Word processor:''' Cut and paste the page content into a word processor. Copy starting at the title and finishing with the last external link. ===Submission=== * Submit the chapter URL (website address), your Wikiversity user name, and a PDF of the chapter via {{Motivation and emotion/Canvas}} ==Marking criteria== [[File:Balanced scales.svg|right|125px]] Book chapters will be marked against the following criteria. ===Overview (5%)=== * Scenario: Provide an engaging scenario or case study in a feature box, with an illustrative figure * Problem statement: Easy to read and understand outline of the key concepts and explanation of practical/real-world problem to be solved * Focus questions: Establish [[/Focus questions|focus questions]] which align with the sub-title and subsequent heading structure ===Theory (20%)=== * Clearly explain the theoretical framework for understanding the topic * Select the most relevant psychological theories/models that apply to the problem. Depending on the topic, this may involve focusing on a single theory or comparing and contrasting two or more theories. * Use at least the best dozen or so peer-reviewed theory references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Clearly explain and apply the theory(ies) * Include illustrative examples, such as case studies * Demonstrate a critical perspective ===Research (25%)=== * Clearly explain how key, peer-reviewed research findings apply to the problem * Use at least the best dozen or so peer-reviewed research references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Include relevant major reviews (such as systematic reviews and meta-analyses) * [[w:Critical thinking|Critical analyse]] the key research findings, including limitations and implications ===Integration (10%)=== * Integrate discussion of theory and review of relevant research * Use research to critically inform interpretation and application of the theory(ies) ===Conclusion (5%)=== * Clear and concise communication of key points and take-home messages * Aligned with the subtitle and focus questions, with implications for the [[Motivation and emotion/Book/Theme|book theme]] ===Style (20%)=== * Overall ** Present and illustrate the problem and knowledge in an interesting way, using a logical structure, clear layout, correct spelling and grammar, and [[APA style]] ** [[/Readability|Readable]] for a layperson interested in psychological science ** Address the [[#Theme|book theme]] by providing practical, academically sound, self-improvement information ** Address an international audience (i.e., avoid an overly local or national perspective) ** Use default wiki style for paragraph alignment, font colour, type, and size, and heading styles ** Use Australian spelling (e.g., hypothesise, behaviour, fulfilment) rather than American spelling (e.g., hypothesize, behavior, fulfillment) ** Correct grammar (e.g., see [[/Writing tips|writing tips]]) * Structure ** Use a logical heading structure that aligns with the focus questions ** Use [https://www.masterclass.com/articles/sentence-case-explained sentence casing] throughout, including for headings and sub-headings ** Use the default heading style (e.g., do not add italics and/or bold) ** Sub-headings are optional *** Avoid having sections with a single sub-heading — each section should contain 0 or 2+ sub-headings. *** If sub-headings are used, provides at least 1 introductory paragraph before branching into sub-sections. * Sentences ** [[w:Narration#Narrative point of view|Narrative point of view]][https://www.grammarly.com/blog/first-second-and-third-person/]: In the main text, use [[w:Narration#Third-person|3rd person perspective]] (e.g., "it", "they"). Where [[w:Aside|aside]]s are used, such as examples, case studies, and feature boxes, [[w:First-person narrative|1st person perspective]] (e.g., "I" and "we") and/or [[w:Narration#Second-person|2nd person perspective]] (e.g., "you") can work well. * Paragraphs ** A well-constructed paragraph is generally 3 to 5 sentences (opening sentence, body sentences, and a concluding/linking sentence). Avoid one-sentence paragraphs and overly long paragraphs. ** Paragraphs flow logically * Use APA style (as much as reasonably possible), paying particular attention to: ** citations ** references (especially capitalisation, italicisation, and providing hyperlinked dois) ** table and figure captions ** quotes (include page numbers) * Citations ** Claims need citations using APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style throughout the chapter — don't mix and match. For most psychology students, APA style will be the choice. ** Maximum of 3 citations per point (i.e., avoid 4 or more citations together). * References ** List all cited academic references in APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style. ** Non-academic sources are not used in references. They can be included in the external links section. ===Learning features (5%)=== * Embed interactive learning features such as scenarios/case studies/examples, feature boxes, figures, quizzes, links to relevant Wikipedia and Wikipedia pages, as well as links to key resources via the "See also" and "External links" sections * Case studies ** Include 1 or more examples, scenarios, or case studies ** They can be true (if so, include citations) or fictional ** Use these examples to enhance understanding of theory, research, focus questions, and/or take-home messages ** Present in a feature box and include a figure ** Consider using a "progressive case study" (i.e., a case study presented in separate parts which describe, for example, the problem, attempt at change, and resolution/outcomes). ** Examples of chapters which make effective use of case studies: *** [[Motivation and emotion/Book/2019/Emotional abuse|emotional abuse]] (2019) *** [[Motivation and emotion/Book/2019/Food and fear|food and fear]] (2019) *** [[Motivation and emotion/Book/2019/Opioid system and human emotion|opioid system and human emotion]] (2019) *** [[Motivation and emotion/Book/2019/Social support and emotion|social support and emotion]] (2019) * [[Motivation and emotion/Wikiversity/Feature box|Feature boxes]] ** Use to highlight key information, but avoid overuse ** There are various ways of creating coloured boxes, but the [[Template:RoundBoxTop|RoundBox]] template is a good option. * [[Motivation and emotion/Wikiversity/Figures|Figures]] ** Include relevant, accompanying figures (e.g., photos, drawings, diagrams) to facilitate readers' understanding of the concepts ** Figures are accompanied by explanatory captions and be cited at least once in the main text ** For more information, see [[Motivation and emotion/Assessment/Chapter/Figures|How to use figures]]). * [[Help:Links|Links]] ** In-text (embedded) links: Key words and concepts are [[Making links|linked]] to Wikipedia articles and/or related book chapters. Provide in-text wiki links the ''first time'' that key concepts are mentioned. For example: *** [[w:Emotion|emotion]] involves physiological, subjective feeling, motivational, and socially expressive aspects. The syntax for creating this link is <nowiki>[[w:Emotion|emotion]]</nowiki>). It is also possible to link to a section on this same page e.g., &lt;nowiki&gt;[[#Overview|Overview]]&lt;nowiki&gt; will link to the Overview section. *** [[Motivation and emotion/Book/2021/Fitspiration and body image|This chapter]] provides an excellent example of embedded links to Wikiversity pages. ** See also *** Provide interwiki links to key related Wikiversity book chapters and/or Wikipedia articles *** Include source in parentheses ** External links *** Provide at least three links to high quality, relevant external resources *** Include author and/or source in parentheses ** Published academic sources belong in References * [[Motivation and emotion/Wikiversity/Tables|Tables]] ** Use accompanying tables to help organise information and communicate concepts to readers ** Tables are accompanied by explanatory APA style captions and are cited in the body text * [[Help:Quiz|Quizzes]] ** Quiz questions or reflection questions encourage reader engagement ** Focus on core concepts (esp. take-home messages) rather than trivia ** Consider incorporating throughout the chapter {{anchor|Socialcontribution}} {{anchor|Social contribution}} ===Social contribution (10%)=== * '''Actions''': Logged contributions which enhance the quality of other book chapters. Useful actions include: ** '''Edits''': Direct edits which improve past or current chapters (e.g., fix errors, enhance clarity) or flag potential improvements by adding [[Template:Clarification templates|clarification templates]]. [[/Search for chapters to improve|Search for chapters to improve]]. ** '''Comments''': Feedback provided on book chapter [[Help:Talk page|talk page]]s ** '''Media uploads''': Upload free-to-use educational images to [[commons:|Wikimedia Commons]] ** '''{{Motivation and emotion/Canvas}} discussion posts''' * '''Evidence''': ** Provide a [[mw:Help:Lists|numbered list]] with summaries of contributions on your [[Help:User page|Wikiversity user page]], and '''direct links''' that show each change or contribution.<!-- To receive credit, contributions must be publicly logged (i.e., log in to Wikiversity so that the edit is recorded with your user name and time-stamp). Summarise each edit on your user page (in a section called "Social contributions") --> ** More info: [[/Summarising social contributions|summarising social contributions]] * '''Marking''' ** Marking of social contributions will be based on a combination of: *** '''Quantity''': **** Breadth: number of chapters contributed to **** Channels: range of communication channels used *** '''Quality''': **** Depth/extent/thoroughness **** Insightfulness **** Practical value *** '''Timeliness''' — there is generally: **** Greater value in earlier contributions **** Lesser value in last-minute contributions ** Marks will be allocated to each clearly evidenced contribution as follows: *** Minor <= 0.25 *** Moderate 0.50 *** Major 1.00 *** Very significant > 1.00 * '''Bonus marks''' ** Up to 5 bonus marks (out of 100 for the book chapter) will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level. ** Approximately 5% of students receive social contribution bonus marks. ** This could include extensive copyediting of multiple chapters and/or regular feedback or support on multiple chapter discussion pages. It may also involve substantial activity on the UCLearn discussion forum. ==Marking rubric== {{Notice|1=[https://docs.google.com/document/d/1yQd1-IekznJNLwhef-yEBaxKtRR6dAVESWXoTa-ti3c/edit?usp=sharing Marking rubric]}} ==Examples== Examples of high quality [[Motivation and emotion/Book|motivation and emotion book chapters]]: * [[Motivation and emotion/Book/2025/AI use, cognitive load, and motivation|AI use, cognitive load, and motivation]] - How does generative AI reduce cognitive effort, and what are the motivational consequences? (2025) * [[Motivation and emotion/Book/2025/Autonomy and intrinsic motivation in self-determination theory|Autonomy and intrinsic motivation in self-determination theory]]: How does autonomy influence intrinsic motivation according to SDT? (2025) * [[Motivation and emotion/Book/2022/Disappointment|Disappointment]]: What is disappointment, what causes it, and how can it be managed? (2022) * [[Motivation and emotion/Book/2016/Illicit drug taking at music festivals|Illicit drug taking at music festivals]]: What motivates young people to take illicit drugs at music festivals? (2016) * [[Motivation and emotion/Book/2019/Organisational change motivation|Organisational change motivation]]: How can leaders build a culture of agility, adaptability, and resilience to deal with a constantly changing workplace? (2019) * [[Motivation and emotion/Book/2019/Phobias|Phobias]]: What are phobias and how can they be dealt with? (2019) * [[Motivation and emotion/Book/2025/Transactive goal dynamics theory and motivation|Transactive goal dynamics theory and motivation]]: What is transactive goal dynamics theory and how does it impact motivation? (2025) Note that as of 2025, chapters no longer include multimedia presentations. For more examples, see the {{Motivation and emotion/Book/High}}s in the [[Motivation and emotion/Book|lists of previous book chapters]]<!-- and the [[:Category:Motivation and emotion/Book/2022/Top|top chapters of 2022]] -->. ==Licensing== Contributions to Wikiversity are made under a [http://creativecommons.org/licenses/by-sa/4.0/ Creative Commons 4.0 Share-alike] (CC-BY-SA 4.0) license which is irrevocable. This license gives permission for others to edit and re-use, with appropriate acknowledgement. For more information, see the [[wmf:Terms of use|Wikimedia Foundation's Terms of use]]. If you do not wish to contribute your work under this license, discuss [[Motivation and emotion/Assessment/Alternative|alternative assessment options]] with the unit convener. ==See also== * [[/FAQ/]] * [[Motivation and emotion/Book|Previous chapters]] * Marking and feedback ** [[Motivation and emotion/Assessment/Chapter/Feedback|General feedback]] ** [[Template:MEBF|Feedback template]] ** [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing Marking rubric] * [[#Socialcontribution|Social contributions]] ** [[/Search for chapters to improve/]] ** [[/Summarising social contributions/]] * [[Motivation and emotion/Tutorials|Tutorials]] <!-- ** [[Motivation and emotion/Tutorials/Topic selection|Tutorial 01: Topic selection]] --> ** [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2: Wiki editing]] ** [[Motivation and emotion/Tutorials/Functionalist theory and self-tracking#Google Scholar|Tutorial 5: Google Scholar]] ** [[Motivation and emotion/Tutorials/Measuring emotion#Topic development feedback|Tutorial 8: Topic development feedback]] * Wikiversity ** [[/Feature boxes/]] ** [[/Figures/]] ** [[How to find free-to-use images|Find free images]] ** [[/Tables/]] * [[/Writing tips/]] ** [[/How to handle a lack of information/|Handling a lack of information]] ** [[/Readability|Readability]] ** [[Motivation and emotion/Assessment/Using generative AI|Using generative AI]] ** [[/Word count|Word count]] {{Motivation and emotion/Assessment/Navigation}} [[Category:Motivation and emotion/Assessment/Chapter| ]] [[Category:Motivation and emotion guidelines]] mpjnmapypfjmhlguiats4wbsq7tsd6h 2835464 2835463 2026-10-02T06:06:13Z Jtneill 10242 /* Marking and feedback */ Update timing of feedback 2835464 wikitext text/x-wiki {{title|Book chapter — Guidelines}} <div style="text-align: center;">''Collaborative online book chapter authoring'' <!-- ---------------------------------- ---> <!-- Count down --> <!-- ---------------------------------- ---><!-- {{countdown |year = 2026 |month = 10 |day = 12 |hour = 0 |event = this assessment is due }} --><!-- {{Motivation and emotion/Assessment/In development}} --> {{/Contents/}}</div> {{TOCright}} ==Overview== * Weight: 50% * Due {{/Due}} * Tasks ** Author an online [[Motivation and emotion/Book|book chapter]] (up to 4,000 words) that explains key psychological theory and research about a unique, specific motivation or emotion topic. ** Develop the chapter by building on the [[Motivation and emotion/Assessment/Topic|topic development]] plan and addressing feedback. ** Contribute to the development of other book chapters (social contribution). * Follow the [[#Instructions|instructions]] and address the [[#Marking criteria|marking criteria]]. ==Purpose== The purpose of the book chapter is to explain and critically evaluate what psychological science says about a specific motivation or emotion topic, and to demonstrate how this knowledge can be applied to understanding and improving human behaviour in everyday life. ==Marking and feedback== * Submissions will be marked according to the [[#Marking criteria|marking criteria]] and [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing marking rubric]. * Marks will be provided via {{Motivation and emotion/Canvas}} within approximately 3 weeks and prior to the exam. * Up to 5 bonus marks will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level (see [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60 rubric]). * Written feedback about how well the chapter addresses the marking criteria will be available via the topic's Wikiversity discussion page. * Follow up with the [[Motivation and emotion/About/Staff|unit convener]] if you have any questions. ==Extensions and late submissions== * Apply for extension using the unit's online Extension Application Form (see {{Motivation and emotion/Canvas}}) with appropriate documentary evidence. * Submissions will be accepted up to 3 days late (-10% per day). * If you don't submit this assessment it is unlikely that you will pass the unit. ==Learning outcomes== How the unit's [[Motivation and emotion/About/Learning outcomes|learning outcomes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto; vertical-align:top;" |- | style="width:40%;" | '''Learning outcome''' | style="width:60%;" | '''Assessment task''' |- | style="vertical-align:top;" | Integrate theories and current research towards explaining the role of motivation and emotions in human behaviour. | style="vertical-align:top;" | Use the most relevant theories and peer-reviewed research to explain a specific motivation or emotion topic. |- | style="vertical-align:top;" | Critically apply knowledge of motivation or emotion to an indepth understanding of a specific topic in this field. | style="vertical-align:top;" | Explain how psychological science can be applied to a specific motivation or emotion topic. Use figures, examples, and/or other interactive learning features to illustrate how this knowledge can apply to understanding human behaviour in everyday life. |} ==Graduate attributes== How the unit's [[Motivation and emotion/About/Graduate attributes|graduate attributes]] are addressed by this assessment exercise: {| border=1 cellpadding=5 cellspacing="0" background:transparent style="width:90%; margin: auto;" |- ! style="width:20%;" | Category ! style="width:20%;" | Graduate attribute ! style="width:60%;" | Assessment task |- | rowspan="4" style="vertical-align:top;" | '''Be professional''' | style="vertical-align:top;" | Communicate effectively | style="vertical-align:top;" | Review scholarly knowledge in an open, online environment and address feedback. |- | style="vertical-align:top;" | Display initiative and drive | style="vertical-align:top;" | Produce an online book chapter about a novel motivation or emotion topic. |- | style="vertical-align:top;" | Up-to-date knowledge and skills | style="vertical-align:top;" | Utilise the most relevant psychological theory and research to address a practical question. |- | style="vertical-align:top;" | Solve problems via thinking | style="vertical-align:top;" | Use critical thinking to explain how psychological science can address real-world problems. |- | rowspan="3" style="vertical-align:top;" | '''Be a global citizen''' | style="vertical-align:top;" | Informed and balanced | style="vertical-align:top;" | Provide a balanced, critical chapter which is accessible to a lay audience. |- | style="vertical-align:top;" | Communicate diversely | style="vertical-align:top;" | Collaborate with peers to communicate knowledge openly with a global audience. |- | style="vertical-align:top;" | Creative use of technology | style="vertical-align:top;" | Learn how to collaborate using wiki technology. |- | rowspan="2" style="vertical-align:top;" | '''Be a lifelong learner''' | style="vertical-align:top;" | Engage in new ideas | style="vertical-align:top;" | Engage in a collaborative learning culture by incorporating feedback and suggestions. |- | style="vertical-align:top;" | Evaluate and adopt new technology | style="vertical-align:top;" | Experience project work in a collaborative, online editing environment. |} ==Instructions== The book chapter should communicate your understanding of the topic based on the best available psychological theory and research. Explain and apply the most relevant evidence in a clear, engaging, and accessible way. The aim is to demonstrate your ability to synthesise and critically evaluate psychological science in order to understand and respond to a specific motivation or emotion phenomenon. The following instructions should be used to guide the development of the book chapter. ===Theme=== * Chapters should fit the book theme which is "understanding and improving our motivational and emotional lives using psychological science" ===Audience=== * The target audience is a general (non-topic-expert) reader interested in personal growth and development based on knowledge in psychological science (theory and research). This is a [[w:science communication|science communication]] exercise. ===Wikiversity=== * Present the chapter as a single page on the [[Main Page|English Wikiversity]] website. A link to the chapter should appear in the [[Motivation and emotion/Book|table of contents]] along with the lead author's Wikiversity user name ===Topic=== * The title and sub-title must be approved by the [[Motivation and emotion/About/Staff|unit convener]] ===Collaboration and feedback=== * Chapters should be independently developed and written primarily by the lead author, but collaboration is strongly encouraged (e.g., by incorporating useful edits and feedback from others) * [[Motivation and emotion/Assessment/Using generative AI|Generative AI]] may be used with appropriate acknowledgement * Lead authors are encouraged to seek feedback about the chapter during the drafting process (e.g., start a {{Motivation and emotion/Canvas}} discussion thread<!-- (use the chapter title and subtitle in the subject line and include a clickable hyperlink to the chapter in the message)-->) * Feedback is usually best placed on the chapter's wiki discussion page * Feedback on the [[Motivation and emotion/Assessment/Topic|topic development]] (chapter plan) will be provided by the [[Motivation and emotion/About/Staff|unit convener]] ===Length (word count)=== {{Anchor|Wordcount}}{{Anchor|Word count}} * There is no minimum length * Maximum 4,000 words ** There is no additional 10% allowance ** Words beyond the maximum will not be considered for marking purposes ** If the chapter exceeds the maximum word count, see [[/Word count|these suggestions]] for strategies to reduce the length while retaining the key content * What to count: ** Count everything from top to bottom of the editable page (in view mode, not edit mode) including the title, subtitle, headings, text, citations, tables, figures, references, see also, and external links ** Don't count menu text across the top and down the left, or categories at the bottom * How to count: ** '''Wikiversity search:''' Copy the page name text which appears at the top of the Wikiversity page (e.g., ''Motivation and emotion/Book/2026/Self-concept and motivation''). Paste this text into the Wikiversity search bar at the top of the page and select the second option, '''Search for pages containing [your title]'''. The first result should be your book chapter. The search result provides information about the chapter, including its word count. ** '''Google Chrome extension:''' [https://chromewebstore.google.com/detail/word-counter/cbjddaobmdfhbfgdgjocbhklpmclcboe Word Counter]. This extension is an easy, reliable method for counting words on a Wikiversity page. '''Cons:''' UC recently blocked this extension on UC devices. ** '''Website:''' Paste the URL into [https://hsuper.tools/web-page-word-counter Webpage Word Counter]. '''Cons:''' Overcounts by approximately 100 words because it includes top and side menus and other page elements. ** '''Word processor:''' Cut and paste the page content into a word processor. Copy starting at the title and finishing with the last external link. ===Submission=== * Submit the chapter URL (website address), your Wikiversity user name, and a PDF of the chapter via {{Motivation and emotion/Canvas}} ==Marking criteria== [[File:Balanced scales.svg|right|125px]] Book chapters will be marked against the following criteria. ===Overview (5%)=== * Scenario: Provide an engaging scenario or case study in a feature box, with an illustrative figure * Problem statement: Easy to read and understand outline of the key concepts and explanation of practical/real-world problem to be solved * Focus questions: Establish [[/Focus questions|focus questions]] which align with the sub-title and subsequent heading structure ===Theory (20%)=== * Clearly explain the theoretical framework for understanding the topic * Select the most relevant psychological theories/models that apply to the problem. Depending on the topic, this may involve focusing on a single theory or comparing and contrasting two or more theories. * Use at least the best dozen or so peer-reviewed theory references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Clearly explain and apply the theory(ies) * Include illustrative examples, such as case studies * Demonstrate a critical perspective ===Research (25%)=== * Clearly explain how key, peer-reviewed research findings apply to the problem * Use at least the best dozen or so peer-reviewed research references about the topic (e.g., see [[Motivation and emotion/Journals|list of motivation and emotion journals]]) * Include relevant major reviews (such as systematic reviews and meta-analyses) * [[w:Critical thinking|Critical analyse]] the key research findings, including limitations and implications ===Integration (10%)=== * Integrate discussion of theory and review of relevant research * Use research to critically inform interpretation and application of the theory(ies) ===Conclusion (5%)=== * Clear and concise communication of key points and take-home messages * Aligned with the subtitle and focus questions, with implications for the [[Motivation and emotion/Book/Theme|book theme]] ===Style (20%)=== * Overall ** Present and illustrate the problem and knowledge in an interesting way, using a logical structure, clear layout, correct spelling and grammar, and [[APA style]] ** [[/Readability|Readable]] for a layperson interested in psychological science ** Address the [[#Theme|book theme]] by providing practical, academically sound, self-improvement information ** Address an international audience (i.e., avoid an overly local or national perspective) ** Use default wiki style for paragraph alignment, font colour, type, and size, and heading styles ** Use Australian spelling (e.g., hypothesise, behaviour, fulfilment) rather than American spelling (e.g., hypothesize, behavior, fulfillment) ** Correct grammar (e.g., see [[/Writing tips|writing tips]]) * Structure ** Use a logical heading structure that aligns with the focus questions ** Use [https://www.masterclass.com/articles/sentence-case-explained sentence casing] throughout, including for headings and sub-headings ** Use the default heading style (e.g., do not add italics and/or bold) ** Sub-headings are optional *** Avoid having sections with a single sub-heading — each section should contain 0 or 2+ sub-headings. *** If sub-headings are used, provides at least 1 introductory paragraph before branching into sub-sections. * Sentences ** [[w:Narration#Narrative point of view|Narrative point of view]][https://www.grammarly.com/blog/first-second-and-third-person/]: In the main text, use [[w:Narration#Third-person|3rd person perspective]] (e.g., "it", "they"). Where [[w:Aside|aside]]s are used, such as examples, case studies, and feature boxes, [[w:First-person narrative|1st person perspective]] (e.g., "I" and "we") and/or [[w:Narration#Second-person|2nd person perspective]] (e.g., "you") can work well. * Paragraphs ** A well-constructed paragraph is generally 3 to 5 sentences (opening sentence, body sentences, and a concluding/linking sentence). Avoid one-sentence paragraphs and overly long paragraphs. ** Paragraphs flow logically * Use APA style (as much as reasonably possible), paying particular attention to: ** citations ** references (especially capitalisation, italicisation, and providing hyperlinked dois) ** table and figure captions ** quotes (include page numbers) * Citations ** Claims need citations using APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style throughout the chapter — don't mix and match. For most psychology students, APA style will be the choice. ** Maximum of 3 citations per point (i.e., avoid 4 or more citations together). * References ** List all cited academic references in APA style or [[w:Wikipedia:Citing_sources|wiki citation style]]. Only use one style. ** Non-academic sources are not used in references. They can be included in the external links section. ===Learning features (5%)=== * Embed interactive learning features such as scenarios/case studies/examples, feature boxes, figures, quizzes, links to relevant Wikipedia and Wikipedia pages, as well as links to key resources via the "See also" and "External links" sections * Case studies ** Include 1 or more examples, scenarios, or case studies ** They can be true (if so, include citations) or fictional ** Use these examples to enhance understanding of theory, research, focus questions, and/or take-home messages ** Present in a feature box and include a figure ** Consider using a "progressive case study" (i.e., a case study presented in separate parts which describe, for example, the problem, attempt at change, and resolution/outcomes). ** Examples of chapters which make effective use of case studies: *** [[Motivation and emotion/Book/2019/Emotional abuse|emotional abuse]] (2019) *** [[Motivation and emotion/Book/2019/Food and fear|food and fear]] (2019) *** [[Motivation and emotion/Book/2019/Opioid system and human emotion|opioid system and human emotion]] (2019) *** [[Motivation and emotion/Book/2019/Social support and emotion|social support and emotion]] (2019) * [[Motivation and emotion/Wikiversity/Feature box|Feature boxes]] ** Use to highlight key information, but avoid overuse ** There are various ways of creating coloured boxes, but the [[Template:RoundBoxTop|RoundBox]] template is a good option. * [[Motivation and emotion/Wikiversity/Figures|Figures]] ** Include relevant, accompanying figures (e.g., photos, drawings, diagrams) to facilitate readers' understanding of the concepts ** Figures are accompanied by explanatory captions and be cited at least once in the main text ** For more information, see [[Motivation and emotion/Assessment/Chapter/Figures|How to use figures]]). * [[Help:Links|Links]] ** In-text (embedded) links: Key words and concepts are [[Making links|linked]] to Wikipedia articles and/or related book chapters. Provide in-text wiki links the ''first time'' that key concepts are mentioned. For example: *** [[w:Emotion|emotion]] involves physiological, subjective feeling, motivational, and socially expressive aspects. The syntax for creating this link is <nowiki>[[w:Emotion|emotion]]</nowiki>). It is also possible to link to a section on this same page e.g., &lt;nowiki&gt;[[#Overview|Overview]]&lt;nowiki&gt; will link to the Overview section. *** [[Motivation and emotion/Book/2021/Fitspiration and body image|This chapter]] provides an excellent example of embedded links to Wikiversity pages. ** See also *** Provide interwiki links to key related Wikiversity book chapters and/or Wikipedia articles *** Include source in parentheses ** External links *** Provide at least three links to high quality, relevant external resources *** Include author and/or source in parentheses ** Published academic sources belong in References * [[Motivation and emotion/Wikiversity/Tables|Tables]] ** Use accompanying tables to help organise information and communicate concepts to readers ** Tables are accompanied by explanatory APA style captions and are cited in the body text * [[Help:Quiz|Quizzes]] ** Quiz questions or reflection questions encourage reader engagement ** Focus on core concepts (esp. take-home messages) rather than trivia ** Consider incorporating throughout the chapter {{anchor|Socialcontribution}} {{anchor|Social contribution}} ===Social contribution (10%)=== * '''Actions''': Logged contributions which enhance the quality of other book chapters. Useful actions include: ** '''Edits''': Direct edits which improve past or current chapters (e.g., fix errors, enhance clarity) or flag potential improvements by adding [[Template:Clarification templates|clarification templates]]. [[/Search for chapters to improve|Search for chapters to improve]]. ** '''Comments''': Feedback provided on book chapter [[Help:Talk page|talk page]]s ** '''Media uploads''': Upload free-to-use educational images to [[commons:|Wikimedia Commons]] ** '''{{Motivation and emotion/Canvas}} discussion posts''' * '''Evidence''': ** Provide a [[mw:Help:Lists|numbered list]] with summaries of contributions on your [[Help:User page|Wikiversity user page]], and '''direct links''' that show each change or contribution.<!-- To receive credit, contributions must be publicly logged (i.e., log in to Wikiversity so that the edit is recorded with your user name and time-stamp). Summarise each edit on your user page (in a section called "Social contributions") --> ** More info: [[/Summarising social contributions|summarising social contributions]] * '''Marking''' ** Marking of social contributions will be based on a combination of: *** '''Quantity''': **** Breadth: number of chapters contributed to **** Channels: range of communication channels used *** '''Quality''': **** Depth/extent/thoroughness **** Insightfulness **** Practical value *** '''Timeliness''' — there is generally: **** Greater value in earlier contributions **** Lesser value in last-minute contributions ** Marks will be allocated to each clearly evidenced contribution as follows: *** Minor <= 0.25 *** Moderate 0.50 *** Major 1.00 *** Very significant > 1.00 * '''Bonus marks''' ** Up to 5 bonus marks (out of 100 for the book chapter) will be awarded in exceptional circumstances where social contributions are above and beyond those required for HD-level. ** Approximately 5% of students receive social contribution bonus marks. ** This could include extensive copyediting of multiple chapters and/or regular feedback or support on multiple chapter discussion pages. It may also involve substantial activity on the UCLearn discussion forum. ==Marking rubric== {{Notice|1=[https://docs.google.com/document/d/1yQd1-IekznJNLwhef-yEBaxKtRR6dAVESWXoTa-ti3c/edit?usp=sharing Marking rubric]}} ==Examples== Examples of high quality [[Motivation and emotion/Book|motivation and emotion book chapters]]: * [[Motivation and emotion/Book/2025/AI use, cognitive load, and motivation|AI use, cognitive load, and motivation]] - How does generative AI reduce cognitive effort, and what are the motivational consequences? (2025) * [[Motivation and emotion/Book/2025/Autonomy and intrinsic motivation in self-determination theory|Autonomy and intrinsic motivation in self-determination theory]]: How does autonomy influence intrinsic motivation according to SDT? (2025) * [[Motivation and emotion/Book/2022/Disappointment|Disappointment]]: What is disappointment, what causes it, and how can it be managed? (2022) * [[Motivation and emotion/Book/2016/Illicit drug taking at music festivals|Illicit drug taking at music festivals]]: What motivates young people to take illicit drugs at music festivals? (2016) * [[Motivation and emotion/Book/2019/Organisational change motivation|Organisational change motivation]]: How can leaders build a culture of agility, adaptability, and resilience to deal with a constantly changing workplace? (2019) * [[Motivation and emotion/Book/2019/Phobias|Phobias]]: What are phobias and how can they be dealt with? (2019) * [[Motivation and emotion/Book/2025/Transactive goal dynamics theory and motivation|Transactive goal dynamics theory and motivation]]: What is transactive goal dynamics theory and how does it impact motivation? (2025) Note that as of 2025, chapters no longer include multimedia presentations. For more examples, see the {{Motivation and emotion/Book/High}}s in the [[Motivation and emotion/Book|lists of previous book chapters]]<!-- and the [[:Category:Motivation and emotion/Book/2022/Top|top chapters of 2022]] -->. ==Licensing== Contributions to Wikiversity are made under a [http://creativecommons.org/licenses/by-sa/4.0/ Creative Commons 4.0 Share-alike] (CC-BY-SA 4.0) license which is irrevocable. This license gives permission for others to edit and re-use, with appropriate acknowledgement. For more information, see the [[wmf:Terms of use|Wikimedia Foundation's Terms of use]]. If you do not wish to contribute your work under this license, discuss [[Motivation and emotion/Assessment/Alternative|alternative assessment options]] with the unit convener. ==See also== * [[/FAQ/]] * [[Motivation and emotion/Book|Previous chapters]] * Marking and feedback ** [[Motivation and emotion/Assessment/Chapter/Feedback|General feedback]] ** [[Template:MEBF|Feedback template]] ** [https://docs.google.com/document/d/15NXyApC5i6svEcJAnXv9QeRA-cbojy1m8lKReZgBH60/edit?usp=sharing Marking rubric] * [[#Socialcontribution|Social contributions]] ** [[/Search for chapters to improve/]] ** [[/Summarising social contributions/]] * [[Motivation and emotion/Tutorials|Tutorials]] <!-- ** [[Motivation and emotion/Tutorials/Topic selection|Tutorial 01: Topic selection]] --> ** [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2: Wiki editing]] ** [[Motivation and emotion/Tutorials/Functionalist theory and self-tracking#Google Scholar|Tutorial 5: Google Scholar]] ** [[Motivation and emotion/Tutorials/Measuring emotion#Topic development feedback|Tutorial 8: Topic development feedback]] * Wikiversity ** [[/Feature boxes/]] ** [[/Figures/]] ** [[How to find free-to-use images|Find free images]] ** [[/Tables/]] * [[/Writing tips/]] ** [[/How to handle a lack of information/|Handling a lack of information]] ** [[/Readability|Readability]] ** [[Motivation and emotion/Assessment/Using generative AI|Using generative AI]] ** [[/Word count|Word count]] {{Motivation and emotion/Assessment/Navigation}} [[Category:Motivation and emotion/Assessment/Chapter| ]] [[Category:Motivation and emotion guidelines]] g5b0lhyl1nud9ocp8y2hmhwm2yh6530 1 112595 2835345 2126205 2026-10-01T13:04:23Z Lbeaumont 278565 Added the section: Long Term Possibilities 2835345 wikitext text/x-wiki == Positioning this == Consider adding this text to better motivate and position the curriculum College graduates have brought us the Enron collapse, the BP oil spill, the Chernobyl disaster, subprime mortgages along with the housing foreclosures and near financial collapse that followed, and loss of the Aral Sea. Perhaps knowledge is not enough. Perhaps we need to make wiser choices. --[[User:Lbeaumont|Lbeaumont]] 11:33, 20 April 2011 (UTC) == E. O. Wilson quote == Consider adding this quote, attributed to E. O. Wilson: We are drowning in information, while starving for wisdom. The world henceforth will be run by synthesizers, people able to put together the right information at the right time, think critically about it, and make important choices wisely. --[[User:Lbeaumont|Lbeaumont]] ([[User talk:Lbeaumont|discuss]] • [[Special:Contributions/Lbeaumont|contribs]]) 14:59, 1 March 2020 (UTC) == Long Term Possibilities == Below is an AI generated suggestion for a wisdom-based curriculum. It may offer suggestions for the long-term evolution of this curriculum. what is the role of Wisdom? In an era where generative AI makes information cheap, abundant, and effortless to synthesize, wisdom becomes the ultimate scarce resource. Rather than merely gathering or organizing facts, the human role shifts toward discernment, moral valuation, and epistemic judgment. According to your sources, the role of wisdom is defined across several key dimensions: *The Ultimate Scarce Resource: As information processing costs approach zero, the historical bottleneck of human learning shifts along a clear spectrum: Information → Attention → Understanding → Judgment → Wisdom. While AI excels at pattern extraction and information synthesis, it cannot make curiosity, lived experience, ethical responsibility, or wisdom. *Converting Patterns into Meaningful Action: Wisdom represents the capacity to convert automated pattern recognition into sound judgment—deciding what information actually deserves human attention, evaluating what is true, and determining what is worth doing. *Epistemic Vigilance and Discernment: In an ecosystem flooded with low-signal "human slop" and synthetic text, wisdom acts as a cognitive filter. It requires asking interrogative questions, surfacing unstated assumptions, auditing algorithmic outputs, and evaluating competing evidence rather than passively accepting automated answers. *The Core Mandate for Higher Education: As AI strips away the university's monopoly on knowledge transmission, institutions must re-justify their mission by evolving from "knowledge repositories" into "Wisdom Institutions". Their primary purpose becomes creating environments for organized disagreement, critical challenge, and character formation so that society can convert information into wisdom without surrendering independent thought to algorithms. Ultimately, while AI democratizes cognitive labor and pattern extraction, wisdom remains the irreducibly human capability that ensures faster learning translates into genuine progress rather than accelerated error. 🧭 Would you like to explore how universities can operationalize this "Wisdom Institution" model through specific curricular changes or assessment redesigns? How can universities become 'Wisdom Institutions'? To transform from traditional knowledge repositories into true "Wisdom Institutions," universities must undergo a fundamental shift in their purpose, pedagogy, and institutional metrics. As AI automates information retrieval and synthesis, universities lose their historical monopoly on knowledge transmission. To remain vital, they must pivot toward cultivating capabilities that algorithms cannot replace. Your sources outline several concrete transformations required for universities to become Wisdom Institutions: #Move Up the Cognitive Value Chain Universities can no longer justify their existence by merely storing or delivering facts3. They must guide students along the full cognitive spectrum: Information → Knowledge → Understanding → Judgment → Wisdom → Responsible Action. While AI can process raw data and generate pattern summaries at near-zero cost, human instruction must focus on the higher-order levels: evaluating what information actually means, selecting what matters, and determining what ought to be done. #Shift Evaluation from 'Products of Thought' to 'Process of Thought' Because generative AI can produce polished essays and passing exam responses in seconds, traditional 18th-century assessment metrics have imploded7. Wisdom Institutions must evaluate cognitive stamina, epistemic vigilance, and prompt literacy4more_horiz. Grading shifts toward auditing how students navigate learning cycles—how they formulate interrogative questions, test unstated assumptions, verify AI-generated outputs for bias or hallucinations, and defend their analytical choices in live Socratic dialogue. #Institutionalize 'Organized Disagreement' and Curated Community A Wisdom Institution does not claim a dogmatic monopoly on defining wisdom28. Instead, its legitimacy rests on creating physical and intellectual spaces—a modern "Republic of Letters"—for organized disagreement. Here, claims are systematically questioned → challenged → tested → discussed → revised through evidence, rigorous debate, and plural perspectives2. This environment serves as a crucial bulwark against digital "slop" and echo chambers4. #Reframe the Professor’s Role and Prioritize Applied Judgment The professor's primary mandate shifts from "I know things you don't know" to "I will help you learn how to think about things you don't yet understand". Pedagogy centers on real-world, collaborative problem-solving that software cannot replicate—such as negotiating ethical trade-offs, managing complex team dynamics, and testing physical prototypes. #Overcome Metric Fixation (Goodhart's Law) Universities currently suffer from incentive distortion where proxies—such as publication counts, citation indexes, rankings, and credential volume—have replaced underlying educational purpose9. Becoming a Wisdom Institution requires realigning incentives so that character formation, critical challenge, and long-term societal value take precedence over easily manipulated metrics. #Serve as Society's Continuous Learning Engine Rather than remaining static, Wisdom Institutions act as dynamic feedback loops for society. They investigate emerging real-world challenges across disciplines, deploy AI to synthesize vast evidence bases, expose machine outputs to human critique, test practical solutions, and continuously update collective understanding as results return. 🏛️ Would you like to draft a syllabus module or assignment rubric designed specifically around these "Wisdom Institution" principles? Draft a syllabus module based on these principles. Syllabus Module: Epistemic Vigilance & Algorithmic Auditing Course: Knowledge, Judgment, and Wisdom in the Post-Literate Age Module Title: Module 4: Epistemic Vigilance and Evaluating the Process of Thought Duration: 4 Weeks Module Overview & Rationale As generative AI lowers the cost of information retrieval and pattern synthesis to near zero, the scarce cognitive resource shifts from raw data gathering toward human attention, critical discernment, and wisdom. This module operationalizes the "Wisdom Institution" model by shifting evaluation away from grading static "products of thought" (such as essays or exams) toward assessing the process of thought, cognitive stamina, and epistemic vigilance. Students learn to use AI as an interactive thought partner while developing the auditing workflows required to interrogate machine outputs and verify truth claims. Key Learning Objectives By the end of this module, students will be able to: #Apply Epistemic Literacy: Subject machine outputs to systematic auditing, identifying unstated assumptions, factual hallucinations, structural biases, and missing evidence. #Execute a Complete Learning Cycle: Navigate a structured 10-stage learning workflow—moving from initial AI inquiry to primary source triangulation, pattern extraction, critical comparison, and reflective judgment7. #Engage in Live Dialectical Defense: Defend reasoning paths, explain analytical choices, and respond to counter-evidence during real-time Socratic challenge. #Exercise Applied Judgment: Collaborate in team-based scenarios to resolve complex ethical trade-offs that software cannot replicate. Weekly Pedagogy & Structural Breakdown Week 1: Prompt Literacy & Interrogative Query Design *Focus: Moving from passive consumption to active interrogation. *Seminar Activity: Students design iterative prompt sequences to test AI models on complex topics, using the model as a Socratic "sparring partner" to map competing arguments59. *Instructor Role: Modeling how to ask probing questions that expose algorithmic limitations and unstated premises. Week 2: Epistemic Auditing & Primary Source Triangulation *Focus: Auditing machine summaries against primary sources. *Core Audit Framework: Students apply a 9-point epistemic audit to generated synthesis6: #What specific claim is being made? #What concrete evidence supports it? #What unstated assumptions are embedded? #What perspective or context is missing? #What alternative explanations exist? #Who benefits from this framing? #What evidence would falsify this claim? #What does the model/source fail to know? #What responsible action should follow? *Practical Lab: Comparing AI pattern summaries directly against original historical or scientific texts to detect subtle distortions or hallucinations. Week 3: Organized Disagreement & Live Socratic Defense *Focus: Establishing a "Republic of Letters" bound by evidence and live debate. *Seminar Activity: Students participate in live oral defenses, presenting their audit findings and defending their conclusions against peer and instructor questioning. *Evaluation Focus: Assessing whether students can justify their analytical choices and modify their conclusions when faced with genuine counter-evidence. Week 4: Applied Problem-Solving & Collaborative Judgment *Focus: Translating verified patterns into ethical action. *Team Challenge: Small interdisciplinary groups navigate an unscripted, real-world case study (e.g., policy trade-offs, resource allocation, or technical ethics) requiring human consensus, negotiation, and moral reasoning. Assessment & Grading Framework (Evaluating Process) Traditional final papers are replaced by three process-focused evaluation components: Assessment Component Weight Evaluation Criteria Prompt & Audit Logbook 40% Comprehensive documentation of prompt iterations, identified AI errors/biases, and primary source verification trails. Live Oral Socratic Defense 35% Cognitive stamina, depth of understanding, and ability to defend analytical paths against real-time counter-arguments. Collaborative Applied Project 25% Interdisciplinary negotiation, practical judgment, and ethical decision-making in complex human scenarios. 📋 Would you like me to generate a tailored report or syllabus artifact from this framework that you can download or export? How can universities realign incentives to overcome Goodhart's Law? Goodhart's Law states that when a measure becomes a target, it ceases to be a good measure1. In higher education, this occurs when proxy metrics—such as publication counts, citation indexes, global rankings, student satisfaction scores, and credential volume—replace the university's underlying purpose1. As a result, institutions end up optimizing for publications rather than understanding, credentials rather than education, and rankings rather than societal value1. Because AI can now generate polished end-products in seconds, relying on traditional metric proxies only accelerates this distortion12. To overcome Goodhart's Law, your sources indicate that universities must realign their incentives across several key areas: #Shift Mission from Information Delivery to Wisdom Rather than competing on information transmission—which generative tools have rendered cheap and abundant—universities must move up the cognitive value chain: Information → Knowledge → Understanding → Judgment → Wisdom → Responsible Action34. Institutional incentives should reward the cultivation of human discernment, critical questioning, and ethical judgment rather than raw information acquisition. #Measure the 'Process of Thought' Over 'Products of Thought' Evaluating static essays, exams, or publication counts incentivizes gaming the system12. Incentives must shift toward evaluating the learning cycle itself: *Rewarding epistemic vigilance and prompt-auditing logbooks that track how students check AI outputs for bias, missing evidence, and hallucinations. *Assessing live Socratic defenses and dialectical debates where students must justify their analytical choices against counter-evidence. #Reframe the University as a 'Truth-Testing Institution' Instead of functioning as knowledge repositories, universities should measure their success by their ability to act as Wisdom Institutions and societal learning engines. Incentives should favor environments built for organized disagreement—where claims are systematically questioned, tested across disciplines, and revised against real-world evidence. *Reframe Faculty Incentives Away from 'Publish-or-Perish' Moving away from publication volume or citation gaming requires realigning faculty rewards around mentorship and cognitive guidance1more_horiz. Professors should be evaluated on how effectively they help students learn how to think about complex topics, interrogate unstated assumptions, and navigate unscripted, interdisciplinary challenges. *Prioritize Applied, Collaborative Problem-Solving Assessment and funding incentives should prioritize complex, team-based projects—such as negotiating ethical trade-offs or developing physical prototypes—where student performance depends on managing messy human dynamics and practical judgment that metrics and software cannot easily automate. 🧭 Would you like to explore how a university department could redesign its faculty tenure and promotion criteria to align with these process-oriented, wisdom-based metrics? Tell me more about the Wisdom Institution model The Wisdom Institution model re-imagines the university for an age of AI-driven information abundance. When generative AI can retrieve, explain, and synthesize vast datasets in seconds, the university's historical role as a static "knowledge repository" or information distributor becomes obsolete. Instead of competing on information access, the Wisdom Institution moves up the cognitive value chain—re-orienting its primary mission toward cultivating understanding, judgment, wisdom, and responsible action. The defining pillars of the Wisdom Institution model include: #Moving Up the Cognitive Value Chain Historically, universities held a monopoly on specialized knowledge1. In the AI age, AI tools can explain complex theories, compare perspectives, and generate syntheses on demand1. To retain value, the university must shift focus from lower-level information delivery to higher-order cognitive capabilities: moving systematically from information $\rightarrow$ knowledge $\rightarrow$ understanding, judgment, wisdom, responsible action. #Legitimacy Through Organized Disagreement A Wisdom Institution does not claim a dogmatic monopoly on defining wisdom or truth. Rather, its institutional legitimacy stems from creating spaces for organized disagreement. It provides a curated environment where claims are systematically questioned, challenged, tested, discussed, revised using primary evidence, logical argument, and plural perspectives25. #Functioning as a Truth-Testing Engine Rather than acting merely as an archive of past knowledge, the Wisdom Institution serves as a dynamic, continuous learning engine for society6: #Real-World Investigation: Society encounters complex, ambiguous problems6. #Interdisciplinary Interpretation: Multiple academic disciplines analyze the issue from different angles6. #AI Synthesis & Human Critique: AI models assemble and synthesize massive evidence bases, which human scholars and students then interrogate and challenge. #Experimental Testing & Feedback: Proposed solutions are tested in practice, and real-world results feed back into ongoing research and teaching. #Redefining the Educator's Role In a Wisdom Institution, the professor's role shifts from an authoritative transmitter ("I know things you don't know") to a cognitive guide ("I will help you learn how to think about things you don't yet understand"). Faculty facilitate learning by posing rigorous, interrogative questions: *What evidence would change your mind? *What unstated assumptions are you relying on? *What are the unintended 10-, 20-, or 50-year consequences? *When is it wiser not to act? #Cultivating Epistemic Vigilance and a 'Republic of Letters' The institution acts as a physical and intellectual bulwark against digital "slop" and attention warfare. It builds epistemic vigilance—training learners to audit synthetic outputs for bias and hallucination—while offering a curated community (a modern "Republic of Letters") bound by shared standards of evidence and intellectual honesty. By uniting human judgment with machine processing power, the Wisdom Institution ensures that accelerated learning leads to genuine societal understanding rather than automated error. f3j8fizt21u1g9srly59jlthidazxj4 0 136794 2835377 2833779 2026-10-01T20:09:05Z Young1lim 21186 /* Copilot Notes */ 2835377 wikitext text/x-wiki This course belongs to the [[Electrical & Computer Engineering Studies]] == Introduction == * Introduction ([[Media:SysP.Intro.20161128.pdf|pdf]]) == File System == * File System ([[Media:SysP.FileSystem.20251023.pdf|pdf]]) * File Pointer ([[Media:SysP..FilePointer.20161103.pdf|pdf]]) * System Calls ([[Media:SysP.File.SysCall.20161128.pdf|pdf]]) * File IO ([[Media:SysP.FileIO.20251023.pdf|pdf]]) === Copilot Notes === * File System ([[Media:glibcFileSystem.20251029-2.pdf|pdf]]) * File Descriptor Table ([[Media:CP.File.Descriptor.20260811.pdf|pdf]]) * File Buffer ([[Media:glibcFileBuffer.20251025-2.pdf|pdf]]) * File IO ([[Media:glibcFileIO.20251025-2.pdf|pdf]]) * File Permission ([[Media:glibcFilePerm.20260121.pdf|pdf]]) * File Control ([[Media:CP.FileCntl.20260428.pdf|pdf]]) :- Overview ([[Media:CP.FileCntl.A.20260824.pdf|pdf]]) :- Duplicating ([[Media:CP.FileCntl.B.20260921.pdf|pdf]]) :- Locking ([[Media:CP.FileCntl.B.20260504.pdf|pdf]]) :- IO ([[Media:CP.FileCntl.C.20260501.pdf|pdf]]) <br> <br> == Process == * Process ([[Media:SysP.Process.20251120.pdf|pdf]]) * Fork ([[Media:SysP.Fork.20251126.pdf|pdf]]) * Copilot: Process Information ([[Media:glibc.Process.1Info.20251101.pdf|pdf]]) * Copilot: Process Control ([[Media:glibc.Process.2Control.20251103.pdf|pdf]]) * Copilot: Process Execution ([[Media:glibc.Proc.3Exec.20251105.pdf|pdf]]) * Copilot: Process Fork ([[Media:glibc.Proc.4Fork.20251106.pdf|pdf]]) * Copilot: Process Context Switching ([[Media:glibc.Proc.5Context.20251107.pdf|pdf]]) * Copilot: Process Exec family of functions ([[Media:glibc.Proc.6ExecCall.20251112.pdf|pdf]]) * Copilot: Process Wait family of functions ([[Media:glibc.Proc.7WaitCall.20251112.pdf|pdf]]) * Copilot: Process Exit ([[Media:glibc.Proc.8Exit.20251113.pdf|pdf]]) </br> == Inter Process Communication== === Signal === * Signal ([[Media:SysP.7.A.Signal.20121206.pdf|pdf]]) * Copilot: Signal 1. Alarm ([[Media:glibc.Signal.Alarm.20251201.pdf|pdf]]) * Copilot: Signal 2. Other Functions ([[Media:glibc.Signal.2Other.20251205.pdf|pdf]]) </br> === Pipe === * Pipe ([[Media:SysP.3.A.IPC.20121115.pdf|pdf]]) * Copilot: Pipe 1. A Special File ([[Media:glibc.Pipe.File.20260307.pdf|pdf]]) </br> === System V IPC === * Message Queue ([[Media:SysP.5.A.MessageQ.20121213.pdf|pdf]]) * Shared Memory ([[Media:SysP.8.A.SharedMem.20121227.pdf|pdf]]) * Semaphore ([[Media:SysP.6.A.Semaphore.20251215.pdf|pdf]]) </br> * Copilot: Message Queue ([[Media:glibc.MessageQ.20251202.pdf|pdf]]) * Copilot: Shared Memory ([[Media:glibc.SharedMem.20251203.pdf|pdf]]) * Copilot: Semaphore ([[Media:glibc.Semaphore.20251215.pdf|pdf]]) </br> === Socket === * Socket ([[Media:SysP.4.A.Socket.20121122.pdf|pdf]]) </br> == Thread == * POSIX thread (pthread) ([[Media:SysP.9.A.Pthread.20130225.pdf|pdf]]) ==External links== * [http://www.tldp.org/LDP/tlk/tlk.html The Linux Kernel] * [http://www.tldp.org/LDP/lpg/lpg.html The Linux Programmer's Guide] * [http://www.cs.cf.ac.uk/Dave/C/ Programming in C - UNIX System Calls and Subroutines using C.] * [http://www.cs.cmu.edu/afs/cs/academic/class/15492-f07/www/pthreads.html POSIX thread (pthread) libraries] * [https://computing.llnl.gov/tutorials/pthreads/#Thread POSIX Threads Programming] [[Category:Linux]] [[Category:Computer programming]] [[Category:C programming language]] d0sx8pcd64h9bgrz1i7d6npnuvqnlgq 2835379 2835377 2026-10-01T20:14:54Z Young1lim 21186 /* Copilot Notes */ 2835379 wikitext text/x-wiki This course belongs to the [[Electrical & Computer Engineering Studies]] == Introduction == * Introduction ([[Media:SysP.Intro.20161128.pdf|pdf]]) == File System == * File System ([[Media:SysP.FileSystem.20251023.pdf|pdf]]) * File Pointer ([[Media:SysP..FilePointer.20161103.pdf|pdf]]) * System Calls ([[Media:SysP.File.SysCall.20161128.pdf|pdf]]) * File IO ([[Media:SysP.FileIO.20251023.pdf|pdf]]) === Copilot Notes === * File System ([[Media:glibcFileSystem.20251029-2.pdf|pdf]]) * File Descriptor Table ([[Media:CP.File.Descriptor.20260811.pdf|pdf]]) * File Buffer ([[Media:glibcFileBuffer.20251025-2.pdf|pdf]]) * File IO ([[Media:glibcFileIO.20251025-2.pdf|pdf]]) * File Permission ([[Media:glibcFilePerm.20260121.pdf|pdf]]) * File Control ([[Media:CP.FileCntl.20260428.pdf|pdf]]) :- Overview ([[Media:CP.FileCntl.A.20260824.pdf|pdf]]) :- Duplicating ([[Media:CP.FileCntl.B.20260922.pdf|pdf]]) :- Locking ([[Media:CP.FileCntl.B.20260504.pdf|pdf]]) :- IO ([[Media:CP.FileCntl.C.20260501.pdf|pdf]]) <br> <br> == Process == * Process ([[Media:SysP.Process.20251120.pdf|pdf]]) * Fork ([[Media:SysP.Fork.20251126.pdf|pdf]]) * Copilot: Process Information ([[Media:glibc.Process.1Info.20251101.pdf|pdf]]) * Copilot: Process Control ([[Media:glibc.Process.2Control.20251103.pdf|pdf]]) * Copilot: Process Execution ([[Media:glibc.Proc.3Exec.20251105.pdf|pdf]]) * Copilot: Process Fork ([[Media:glibc.Proc.4Fork.20251106.pdf|pdf]]) * Copilot: Process Context Switching ([[Media:glibc.Proc.5Context.20251107.pdf|pdf]]) * Copilot: Process Exec family of functions ([[Media:glibc.Proc.6ExecCall.20251112.pdf|pdf]]) * Copilot: Process Wait family of functions ([[Media:glibc.Proc.7WaitCall.20251112.pdf|pdf]]) * Copilot: Process Exit ([[Media:glibc.Proc.8Exit.20251113.pdf|pdf]]) </br> == Inter Process Communication== === Signal === * Signal ([[Media:SysP.7.A.Signal.20121206.pdf|pdf]]) * Copilot: Signal 1. Alarm ([[Media:glibc.Signal.Alarm.20251201.pdf|pdf]]) * Copilot: Signal 2. Other Functions ([[Media:glibc.Signal.2Other.20251205.pdf|pdf]]) </br> === Pipe === * Pipe ([[Media:SysP.3.A.IPC.20121115.pdf|pdf]]) * Copilot: Pipe 1. A Special File ([[Media:glibc.Pipe.File.20260307.pdf|pdf]]) </br> === System V IPC === * Message Queue ([[Media:SysP.5.A.MessageQ.20121213.pdf|pdf]]) * Shared Memory ([[Media:SysP.8.A.SharedMem.20121227.pdf|pdf]]) * Semaphore ([[Media:SysP.6.A.Semaphore.20251215.pdf|pdf]]) </br> * Copilot: Message Queue ([[Media:glibc.MessageQ.20251202.pdf|pdf]]) * Copilot: Shared Memory ([[Media:glibc.SharedMem.20251203.pdf|pdf]]) * Copilot: Semaphore ([[Media:glibc.Semaphore.20251215.pdf|pdf]]) </br> === Socket === * Socket ([[Media:SysP.4.A.Socket.20121122.pdf|pdf]]) </br> == Thread == * POSIX thread (pthread) ([[Media:SysP.9.A.Pthread.20130225.pdf|pdf]]) ==External links== * [http://www.tldp.org/LDP/tlk/tlk.html The Linux Kernel] * [http://www.tldp.org/LDP/lpg/lpg.html The Linux Programmer's Guide] * [http://www.cs.cf.ac.uk/Dave/C/ Programming in C - UNIX System Calls and Subroutines using C.] * [http://www.cs.cmu.edu/afs/cs/academic/class/15492-f07/www/pthreads.html POSIX thread (pthread) libraries] * [https://computing.llnl.gov/tutorials/pthreads/#Thread POSIX Threads Programming] [[Category:Linux]] [[Category:Computer programming]] [[Category:C programming language]] rty2xvsdqrxxm6pyo5r6sqglzl8x8f6 2835381 2835379 2026-10-01T20:15:56Z Young1lim 21186 /* Copilot Notes */ 2835381 wikitext text/x-wiki This course belongs to the [[Electrical & Computer Engineering Studies]] == Introduction == * Introduction ([[Media:SysP.Intro.20161128.pdf|pdf]]) == File System == * File System ([[Media:SysP.FileSystem.20251023.pdf|pdf]]) * File Pointer ([[Media:SysP..FilePointer.20161103.pdf|pdf]]) * System Calls ([[Media:SysP.File.SysCall.20161128.pdf|pdf]]) * File IO ([[Media:SysP.FileIO.20251023.pdf|pdf]]) === Copilot Notes === * File System ([[Media:glibcFileSystem.20251029-2.pdf|pdf]]) * File Descriptor Table ([[Media:CP.File.Descriptor.20260811.pdf|pdf]]) * File Buffer ([[Media:glibcFileBuffer.20251025-2.pdf|pdf]]) * File IO ([[Media:glibcFileIO.20251025-2.pdf|pdf]]) * File Permission ([[Media:glibcFilePerm.20260121.pdf|pdf]]) * File Control ([[Media:CP.FileCntl.20260428.pdf|pdf]]) :- Overview ([[Media:CP.FileCntl.A.20260824.pdf|pdf]]) :- Duplicating ([[Media:CP.FileCntl.B.20260928.pdf|pdf]]) :- Locking ([[Media:CP.FileCntl.B.20260504.pdf|pdf]]) :- IO ([[Media:CP.FileCntl.C.20260501.pdf|pdf]]) <br> <br> == Process == * Process ([[Media:SysP.Process.20251120.pdf|pdf]]) * Fork ([[Media:SysP.Fork.20251126.pdf|pdf]]) * Copilot: Process Information ([[Media:glibc.Process.1Info.20251101.pdf|pdf]]) * Copilot: Process Control ([[Media:glibc.Process.2Control.20251103.pdf|pdf]]) * Copilot: Process Execution ([[Media:glibc.Proc.3Exec.20251105.pdf|pdf]]) * Copilot: Process Fork ([[Media:glibc.Proc.4Fork.20251106.pdf|pdf]]) * Copilot: Process Context Switching ([[Media:glibc.Proc.5Context.20251107.pdf|pdf]]) * Copilot: Process Exec family of functions ([[Media:glibc.Proc.6ExecCall.20251112.pdf|pdf]]) * Copilot: Process Wait family of functions ([[Media:glibc.Proc.7WaitCall.20251112.pdf|pdf]]) * Copilot: Process Exit ([[Media:glibc.Proc.8Exit.20251113.pdf|pdf]]) </br> == Inter Process Communication== === Signal === * Signal ([[Media:SysP.7.A.Signal.20121206.pdf|pdf]]) * Copilot: Signal 1. Alarm ([[Media:glibc.Signal.Alarm.20251201.pdf|pdf]]) * Copilot: Signal 2. Other Functions ([[Media:glibc.Signal.2Other.20251205.pdf|pdf]]) </br> === Pipe === * Pipe ([[Media:SysP.3.A.IPC.20121115.pdf|pdf]]) * Copilot: Pipe 1. A Special File ([[Media:glibc.Pipe.File.20260307.pdf|pdf]]) </br> === System V IPC === * Message Queue ([[Media:SysP.5.A.MessageQ.20121213.pdf|pdf]]) * Shared Memory ([[Media:SysP.8.A.SharedMem.20121227.pdf|pdf]]) * Semaphore ([[Media:SysP.6.A.Semaphore.20251215.pdf|pdf]]) </br> * Copilot: Message Queue ([[Media:glibc.MessageQ.20251202.pdf|pdf]]) * Copilot: Shared Memory ([[Media:glibc.SharedMem.20251203.pdf|pdf]]) * Copilot: Semaphore ([[Media:glibc.Semaphore.20251215.pdf|pdf]]) </br> === Socket === * Socket ([[Media:SysP.4.A.Socket.20121122.pdf|pdf]]) </br> == Thread == * POSIX thread (pthread) ([[Media:SysP.9.A.Pthread.20130225.pdf|pdf]]) ==External links== * [http://www.tldp.org/LDP/tlk/tlk.html The Linux Kernel] * [http://www.tldp.org/LDP/lpg/lpg.html The Linux Programmer's Guide] * [http://www.cs.cf.ac.uk/Dave/C/ Programming in C - UNIX System Calls and Subroutines using C.] * [http://www.cs.cmu.edu/afs/cs/academic/class/15492-f07/www/pthreads.html POSIX thread (pthread) libraries] * [https://computing.llnl.gov/tutorials/pthreads/#Thread POSIX Threads Programming] [[Category:Linux]] [[Category:Computer programming]] [[Category:C programming language]] 3vc2qr5zc0c2b7yf4i2skjuq9z7snjl 2835383 2835381 2026-10-01T20:17:11Z Young1lim 21186 /* Copilot Notes */ 2835383 wikitext text/x-wiki This course belongs to the [[Electrical & Computer Engineering Studies]] == Introduction == * Introduction ([[Media:SysP.Intro.20161128.pdf|pdf]]) == File System == * File System ([[Media:SysP.FileSystem.20251023.pdf|pdf]]) * File Pointer ([[Media:SysP..FilePointer.20161103.pdf|pdf]]) * System Calls ([[Media:SysP.File.SysCall.20161128.pdf|pdf]]) * File IO ([[Media:SysP.FileIO.20251023.pdf|pdf]]) === Copilot Notes === * File System ([[Media:glibcFileSystem.20251029-2.pdf|pdf]]) * File Descriptor Table ([[Media:CP.File.Descriptor.20260811.pdf|pdf]]) * File Buffer ([[Media:glibcFileBuffer.20251025-2.pdf|pdf]]) * File IO ([[Media:glibcFileIO.20251025-2.pdf|pdf]]) * File Permission ([[Media:glibcFilePerm.20260121.pdf|pdf]]) * File Control ([[Media:CP.FileCntl.20260428.pdf|pdf]]) :- Overview ([[Media:CP.FileCntl.A.20260824.pdf|pdf]]) :- Duplicating ([[Media:CP.FileCntl.B.20260929.pdf|pdf]]) :- Locking ([[Media:CP.FileCntl.B.20260504.pdf|pdf]]) :- IO ([[Media:CP.FileCntl.C.20260501.pdf|pdf]]) <br> <br> == Process == * Process ([[Media:SysP.Process.20251120.pdf|pdf]]) * Fork ([[Media:SysP.Fork.20251126.pdf|pdf]]) * Copilot: Process Information ([[Media:glibc.Process.1Info.20251101.pdf|pdf]]) * Copilot: Process Control ([[Media:glibc.Process.2Control.20251103.pdf|pdf]]) * Copilot: Process Execution ([[Media:glibc.Proc.3Exec.20251105.pdf|pdf]]) * Copilot: Process Fork ([[Media:glibc.Proc.4Fork.20251106.pdf|pdf]]) * Copilot: Process Context Switching ([[Media:glibc.Proc.5Context.20251107.pdf|pdf]]) * Copilot: Process Exec family of functions ([[Media:glibc.Proc.6ExecCall.20251112.pdf|pdf]]) * Copilot: Process Wait family of functions ([[Media:glibc.Proc.7WaitCall.20251112.pdf|pdf]]) * Copilot: Process Exit ([[Media:glibc.Proc.8Exit.20251113.pdf|pdf]]) </br> == Inter Process Communication== === Signal === * Signal ([[Media:SysP.7.A.Signal.20121206.pdf|pdf]]) * Copilot: Signal 1. Alarm ([[Media:glibc.Signal.Alarm.20251201.pdf|pdf]]) * Copilot: Signal 2. Other Functions ([[Media:glibc.Signal.2Other.20251205.pdf|pdf]]) </br> === Pipe === * Pipe ([[Media:SysP.3.A.IPC.20121115.pdf|pdf]]) * Copilot: Pipe 1. A Special File ([[Media:glibc.Pipe.File.20260307.pdf|pdf]]) </br> === System V IPC === * Message Queue ([[Media:SysP.5.A.MessageQ.20121213.pdf|pdf]]) * Shared Memory ([[Media:SysP.8.A.SharedMem.20121227.pdf|pdf]]) * Semaphore ([[Media:SysP.6.A.Semaphore.20251215.pdf|pdf]]) </br> * Copilot: Message Queue ([[Media:glibc.MessageQ.20251202.pdf|pdf]]) * Copilot: Shared Memory ([[Media:glibc.SharedMem.20251203.pdf|pdf]]) * Copilot: Semaphore ([[Media:glibc.Semaphore.20251215.pdf|pdf]]) </br> === Socket === * Socket ([[Media:SysP.4.A.Socket.20121122.pdf|pdf]]) </br> == Thread == * POSIX thread (pthread) ([[Media:SysP.9.A.Pthread.20130225.pdf|pdf]]) ==External links== * [http://www.tldp.org/LDP/tlk/tlk.html The Linux Kernel] * [http://www.tldp.org/LDP/lpg/lpg.html The Linux Programmer's Guide] * [http://www.cs.cf.ac.uk/Dave/C/ Programming in C - UNIX System Calls and Subroutines using C.] * [http://www.cs.cmu.edu/afs/cs/academic/class/15492-f07/www/pthreads.html POSIX thread (pthread) libraries] * [https://computing.llnl.gov/tutorials/pthreads/#Thread POSIX Threads Programming] [[Category:Linux]] [[Category:Computer programming]] [[Category:C programming language]] rqiz7tuky2tu2ccrx623xjeur9lad5y 0 168829 2835497 2830273 2026-10-02T11:09:45Z Dick Bos 24466 cat 2835497 wikitext text/x-wiki ==Contents== * [[/Introduction/]] * [[/Ancient/]] * [[/Middle Ages/]] * [[/Pre-classical: Before Adam/]], [[William Petty]] * [[/Physiocracy/]], [[/Francois Quesnay/]] * [[/Classical Economics/]]: ** [[/Adam Smith/]] ** [[/Jean-Baptiste Say/]] ** [[/Thomas Robert Malthus/]] ** [[David Ricardo]] ** [[/John Stuart Mill/]] * [[/Socialists Before Marx/]] * [[/Karl Marx and Marxism/]]: ** [[Karl Marx]] ** [[Friedrich Engels]] * [[/The Neo-classical Economics: Marginal Revolution/]] * [[/Menger and Austrian Economics/]] * [[/Léon Walras and Vilfredo Pareto: General Equilibrium/]] * [[/Alfred Marshall/]] * [[/Historical school and Institutional Economics/]] * [[/Monetary Theories Before Keynesian Revolution/]] * [[/John Maynard Keynes and Keynesian Revolution/]] * [[/Keynesians after Keynes and Neoclassical Synthesis/]] * [[/Capitalism and Socialism/]] * [[/Econometrics and Mathematical Economics/]] * [[/Economists and Policy/]] * [[/Development of Game Theory/]] * [[/Milton Friedman and Monetarist Counterrevolution/]] * [[/Expansion of the Applications of Economic Analysis/]] * [[/Rational Expectation and After/]] * [[/Economic Growth Theory and Development Economics/]] * [[/International Economics/]] * [[/Postwar Heterodox Economics/]] * [[/Contemporary Economics/]] [[Category:History of Economic Thought|History of Economic Thought]] f8kun17i5nl6m1sjhyro1dt8psnl8tp 2835498 2835497 2026-10-02T11:11:38Z Dick Bos 24466 corr cat 2835498 wikitext text/x-wiki ==Contents== * [[/Introduction/]] * [[/Ancient/]] * [[/Middle Ages/]] * [[/Pre-classical: Before Adam/]], [[William Petty]] * [[/Physiocracy/]], [[/Francois Quesnay/]] * [[/Classical Economics/]]: ** [[/Adam Smith/]] ** [[/Jean-Baptiste Say/]] ** [[/Thomas Robert Malthus/]] ** [[David Ricardo]] ** [[/John Stuart Mill/]] * [[/Socialists Before Marx/]] * [[/Karl Marx and Marxism/]]: ** [[Karl Marx]] ** [[Friedrich Engels]] * [[/The Neo-classical Economics: Marginal Revolution/]] * [[/Menger and Austrian Economics/]] * [[/Léon Walras and Vilfredo Pareto: General Equilibrium/]] * [[/Alfred Marshall/]] * [[/Historical school and Institutional Economics/]] * [[/Monetary Theories Before Keynesian Revolution/]] * [[/John Maynard Keynes and Keynesian Revolution/]] * [[/Keynesians after Keynes and Neoclassical Synthesis/]] * [[/Capitalism and Socialism/]] * [[/Econometrics and Mathematical Economics/]] * [[/Economists and Policy/]] * [[/Development of Game Theory/]] * [[/Milton Friedman and Monetarist Counterrevolution/]] * [[/Expansion of the Applications of Economic Analysis/]] * [[/Rational Expectation and After/]] * [[/Economic Growth Theory and Development Economics/]] * [[/International Economics/]] * [[/Postwar Heterodox Economics/]] * [[/Contemporary Economics/]] [[Category:History of Economic Thought| ]] thdj1y3sbn8l3mg20tr6sketxfkez5v 102 207548 2835434 1854691 2026-10-02T03:26:04Z ~2026-52776-53 3111976 2835434 wikitext text/x-wiki <!-- Add interesting {{Titleparts|1}} facts [[{{Titleparts|2}}/Did You Know: |here]] --> * The [[Wikipedia:Z1 (computer)|Z1]], created by [[Wikipedia:Konrad Zuse|Konrad Zuse]] in 1936-1938, was the first modern computer. 784m13rnpj1lg18zr4xn809miuladnf 2835477 2835434 2026-10-02T08:51:59Z PieWriter 3039865 Restored revision 1854691 by [[Special:Contributions/Nigos|Nigos]] ([[User talk:Nigos|talk]]) (TwinkleGlobal) 2835477 wikitext text/x-wiki <!-- Add interesting {{Titleparts|1}} facts [[{{Titleparts|2}}/Did You Know|here]] --> * The [[Wikipedia:Z1 (computer)|Z1]], created by [[Wikipedia:Konrad Zuse|Konrad Zuse]] in 1936-1938, was the first modern computer. h03x5bckjkbv0bzwq97p1stxn13kx9o 0 212733 2835386 2833729 2026-10-01T21:09:39Z Young1lim 21186 /* Using Libraries */ 2835386 wikitext text/x-wiki ==''' Part I '''== <!----------------------------------------------------------------------> === Introduction === * Overview * Memory * Number <!----------------------------------------------------------------------> === Python for C programmers === * Hello, World! ([[Media:CProg.Hello.1A.20230406.pdf |pdf]]) * Statement Level ([[Media:CProg.Statement.1A.20230509.pdf |pdf]]) * Output with print * Formatted output * File IO <!----------------------------------------------------------------------> === Using Libraries === * Scripts ([[Media:Python.Work2.Script.1A.20231129.pdf |pdf]]) * Modules ([[Media:Python.Work2.Module.1A.20231216.pdf |pdf]]) * Packages ([[Media:Python.Work2.Package.1A.20241207.pdf |pdf]]) * Libraries ([[Media:Python.Work2.Library.1A.20260921.pdf |A]], [[Media:Python.Work2.Library.1B.20260720.pdf |B]]) * Namespaces ([[Media:Python.Work2.Scope.1A.20231021.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Repetition === * Control ([[Media:Python.Repeat1.Control.1.A.20230314.pdf |pdf]]) * Loop ([[Media:Repeat2.Loop.1A.20230401.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling a Big Work === * Functions ([[Media:Python.Work1.Function.1A.20230529.pdf |pdf]]) * Lambda ([[Media:Python.Work2.Lambda.1A.20230705.pdf |pdf]]) * Type Annotations ([[Media:Python.Work2.AtypeAnnot.1A.20230817.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Series of Data === * Arrays ([[Media:Python.Series1.Array.1A.pdf |pdf]]) * Tuples ([[Media:Python.Series2.Tuple.1A.pdf |pdf]]) * Lists ([[Media:Python.Series3.List.1A.pdf |pdf]]) * Tuples ([[Media:Python.Series4.Tuple.1A.pdf |pdf]]) * Sets ([[Media:Python.Series5.Set.1A.pdf |pdf]]) * Dictionary ([[Media:Python.Series6.Dictionary.1A.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Various Kinds of Data === * Types * Operators ([[Media:Python.Data3.Operators.1.A.pdf |pdf]]) * Files ([[Media:Python.Data4.File.1.A.pdf |pdf]]) <!----------------------------------------------------------------------> === Class and Objects === * Classes & Objects ([[Media:Python.Work2.Class.1A.20230906.pdf |pdf]]) * Inheritance <!----------------------------------------------------------------------> </br> == Python in Numerical Analysis == </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] ==External links== * [http://www.southampton.ac.uk/~fangohr/training/python/pdfs/Python-for-Computational-Science-and-Engineering.pdf Python and Computational Science and Engineering] 4wrpylus7kcp8nk1vezexmdneie2f6l 2835388 2835386 2026-10-01T21:10:55Z Young1lim 21186 /* Using Libraries */ 2835388 wikitext text/x-wiki ==''' Part I '''== <!----------------------------------------------------------------------> === Introduction === * Overview * Memory * Number <!----------------------------------------------------------------------> === Python for C programmers === * Hello, World! ([[Media:CProg.Hello.1A.20230406.pdf |pdf]]) * Statement Level ([[Media:CProg.Statement.1A.20230509.pdf |pdf]]) * Output with print * Formatted output * File IO <!----------------------------------------------------------------------> === Using Libraries === * Scripts ([[Media:Python.Work2.Script.1A.20231129.pdf |pdf]]) * Modules ([[Media:Python.Work2.Module.1A.20231216.pdf |pdf]]) * Packages ([[Media:Python.Work2.Package.1A.20241207.pdf |pdf]]) * Libraries ([[Media:Python.Work2.Library.1A.20260922.pdf |A]], [[Media:Python.Work2.Library.1B.20260720.pdf |B]]) * Namespaces ([[Media:Python.Work2.Scope.1A.20231021.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Repetition === * Control ([[Media:Python.Repeat1.Control.1.A.20230314.pdf |pdf]]) * Loop ([[Media:Repeat2.Loop.1A.20230401.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling a Big Work === * Functions ([[Media:Python.Work1.Function.1A.20230529.pdf |pdf]]) * Lambda ([[Media:Python.Work2.Lambda.1A.20230705.pdf |pdf]]) * Type Annotations ([[Media:Python.Work2.AtypeAnnot.1A.20230817.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Series of Data === * Arrays ([[Media:Python.Series1.Array.1A.pdf |pdf]]) * Tuples ([[Media:Python.Series2.Tuple.1A.pdf |pdf]]) * Lists ([[Media:Python.Series3.List.1A.pdf |pdf]]) * Tuples ([[Media:Python.Series4.Tuple.1A.pdf |pdf]]) * Sets ([[Media:Python.Series5.Set.1A.pdf |pdf]]) * Dictionary ([[Media:Python.Series6.Dictionary.1A.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Various Kinds of Data === * Types * Operators ([[Media:Python.Data3.Operators.1.A.pdf |pdf]]) * Files ([[Media:Python.Data4.File.1.A.pdf |pdf]]) <!----------------------------------------------------------------------> === Class and Objects === * Classes & Objects ([[Media:Python.Work2.Class.1A.20230906.pdf |pdf]]) * Inheritance <!----------------------------------------------------------------------> </br> == Python in Numerical Analysis == </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] ==External links== * [http://www.southampton.ac.uk/~fangohr/training/python/pdfs/Python-for-Computational-Science-and-Engineering.pdf Python and Computational Science and Engineering] tsihj4bcf0556qeyglcefqi7f215xom 2835390 2835388 2026-10-01T21:12:04Z Young1lim 21186 /* Using Libraries */ 2835390 wikitext text/x-wiki ==''' Part I '''== <!----------------------------------------------------------------------> === Introduction === * Overview * Memory * Number <!----------------------------------------------------------------------> === Python for C programmers === * Hello, World! ([[Media:CProg.Hello.1A.20230406.pdf |pdf]]) * Statement Level ([[Media:CProg.Statement.1A.20230509.pdf |pdf]]) * Output with print * Formatted output * File IO <!----------------------------------------------------------------------> === Using Libraries === * Scripts ([[Media:Python.Work2.Script.1A.20231129.pdf |pdf]]) * Modules ([[Media:Python.Work2.Module.1A.20231216.pdf |pdf]]) * Packages ([[Media:Python.Work2.Package.1A.20241207.pdf |pdf]]) * Libraries ([[Media:Python.Work2.Library.1A.20260928.pdf |A]], [[Media:Python.Work2.Library.1B.20260720.pdf |B]]) * Namespaces ([[Media:Python.Work2.Scope.1A.20231021.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Repetition === * Control ([[Media:Python.Repeat1.Control.1.A.20230314.pdf |pdf]]) * Loop ([[Media:Repeat2.Loop.1A.20230401.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling a Big Work === * Functions ([[Media:Python.Work1.Function.1A.20230529.pdf |pdf]]) * Lambda ([[Media:Python.Work2.Lambda.1A.20230705.pdf |pdf]]) * Type Annotations ([[Media:Python.Work2.AtypeAnnot.1A.20230817.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Series of Data === * Arrays ([[Media:Python.Series1.Array.1A.pdf |pdf]]) * Tuples ([[Media:Python.Series2.Tuple.1A.pdf |pdf]]) * Lists ([[Media:Python.Series3.List.1A.pdf |pdf]]) * Tuples ([[Media:Python.Series4.Tuple.1A.pdf |pdf]]) * Sets ([[Media:Python.Series5.Set.1A.pdf |pdf]]) * Dictionary ([[Media:Python.Series6.Dictionary.1A.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Various Kinds of Data === * Types * Operators ([[Media:Python.Data3.Operators.1.A.pdf |pdf]]) * Files ([[Media:Python.Data4.File.1.A.pdf |pdf]]) <!----------------------------------------------------------------------> === Class and Objects === * Classes & Objects ([[Media:Python.Work2.Class.1A.20230906.pdf |pdf]]) * Inheritance <!----------------------------------------------------------------------> </br> == Python in Numerical Analysis == </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] ==External links== * [http://www.southampton.ac.uk/~fangohr/training/python/pdfs/Python-for-Computational-Science-and-Engineering.pdf Python and Computational Science and Engineering] mgvwyxam0rdx09p2c7ewxlyn1lvayyn 2835392 2835390 2026-10-01T21:13:01Z Young1lim 21186 /* Using Libraries */ 2835392 wikitext text/x-wiki ==''' Part I '''== <!----------------------------------------------------------------------> === Introduction === * Overview * Memory * Number <!----------------------------------------------------------------------> === Python for C programmers === * Hello, World! ([[Media:CProg.Hello.1A.20230406.pdf |pdf]]) * Statement Level ([[Media:CProg.Statement.1A.20230509.pdf |pdf]]) * Output with print * Formatted output * File IO <!----------------------------------------------------------------------> === Using Libraries === * Scripts ([[Media:Python.Work2.Script.1A.20231129.pdf |pdf]]) * Modules ([[Media:Python.Work2.Module.1A.20231216.pdf |pdf]]) * Packages ([[Media:Python.Work2.Package.1A.20241207.pdf |pdf]]) * Libraries ([[Media:Python.Work2.Library.1A.20260929.pdf |A]], [[Media:Python.Work2.Library.1B.20260720.pdf |B]]) * Namespaces ([[Media:Python.Work2.Scope.1A.20231021.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Repetition === * Control ([[Media:Python.Repeat1.Control.1.A.20230314.pdf |pdf]]) * Loop ([[Media:Repeat2.Loop.1A.20230401.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling a Big Work === * Functions ([[Media:Python.Work1.Function.1A.20230529.pdf |pdf]]) * Lambda ([[Media:Python.Work2.Lambda.1A.20230705.pdf |pdf]]) * Type Annotations ([[Media:Python.Work2.AtypeAnnot.1A.20230817.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Series of Data === * Arrays ([[Media:Python.Series1.Array.1A.pdf |pdf]]) * Tuples ([[Media:Python.Series2.Tuple.1A.pdf |pdf]]) * Lists ([[Media:Python.Series3.List.1A.pdf |pdf]]) * Tuples ([[Media:Python.Series4.Tuple.1A.pdf |pdf]]) * Sets ([[Media:Python.Series5.Set.1A.pdf |pdf]]) * Dictionary ([[Media:Python.Series6.Dictionary.1A.pdf |pdf]]) <!----------------------------------------------------------------------> === Handling Various Kinds of Data === * Types * Operators ([[Media:Python.Data3.Operators.1.A.pdf |pdf]]) * Files ([[Media:Python.Data4.File.1.A.pdf |pdf]]) <!----------------------------------------------------------------------> === Class and Objects === * Classes & Objects ([[Media:Python.Work2.Class.1A.20230906.pdf |pdf]]) * Inheritance <!----------------------------------------------------------------------> </br> == Python in Numerical Analysis == </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] ==External links== * [http://www.southampton.ac.uk/~fangohr/training/python/pdfs/Python-for-Computational-Science-and-Engineering.pdf Python and Computational Science and Engineering] bv9f208ddhi5kr5kgxok6fvqwsxqji5 0 264910 2835394 2835101 2026-10-01T22:00:33Z Jtneill 10242 2835394 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 4: Psychological needs|fourth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial facilitates interactive discussion about two aspects of [[self-determination theory]]: # basic psychological needs # taxonomy of motivation (intrinsic-extrinsic motivation) ==Needs== Brainstorm and discuss: {{collapse box|'''What are needs?'''|Needs are ''requirements'' (essential) for surviving (biological needs) and thriving (psychological needs).}} {{collapse box|'''How do needs differ from desires, wants, likes etc.?'''|Needs are ''essential'' for survival (e.g., warmth, transport) and well-being whereas desires, wants, likes etc. are motivations for ''non-essential'' stimuli (e.g., an umbrella in the rain, a new car).}} {{collapse box|'''What types of needs are there?'''|'''2-factor''': deficit-based (biological) needs (e.g., thirst, hunger, sleep) and growth-based (psychological) needs (e.g., autonomy, competence, relatedness).<br>'''3-factor''': The Alderfer ERG theory refers to existence, relatedness, and growth needs.<br>'''5-factor''': Maslow's hierarchy of needs has five needs: Physiological, Safety, Belonging & love, Esteem, Self-actualisation}} {{collapse box|'''What are the basic psychological needs?'''|According to self-determination theory:<br>autonomy, competence, and relatedness}} ==Taxonomy of motivation== Discuss: {{collapse box|'''What characterises [[extrinsic motivation]]? Examples?'''| * External (environmental) reasons for behaving * Caused by carrots (incentives and rewards e.g., praise) or sticks (threats and punishments e.g., insults).}} {{collapse box|'''What characterises [[intrinsic motivation]]? Examples?'''| * Internal reasons for behaving * Involves volition (i.e., ''I want to'') and enjoyment (e.g., hobbies) * External influences are absent.}} {{collapse box|'''Advantages of the I-E motivation distinction?'''| * Breaks motivation down into types * Simple and easy to understand * Helps with research designs}} {{collapse box|'''Disadvantages of the I-E motivation distinction?'''| * A dichotomous distinction is overly simplistic * Motivational sources are often complex and dynamic, involving aspects of both intrinsic and extrinsic motivation}} {{collapse box|'''Types of motivation described by Deci and Ryan (2000)'''| * Amotivation * Extrinsic motivation ** External regulation ** Introjection ** Identification ** Integration * Intrinsic motivation }} <!-- Handout a [https://drive.google.com/file/d/0B2N4zSp4hmN9WHEwSmoyUWhOZm8/view?usp=sharing blanked version of Deci and Ryan's taxonomy] and facilitate the class to define, discuss, and generate examples for each of the components:--> == Quiz: Identify the type of motivation == This 12-item quiz tests your knowledge of Deci and Ryan's taxonomy of motivation. [[/Quiz|Go to quiz]]. Alternative (advenced) exercise: What strategies can motivate exercise behaviours? * Brainstorm ways of motivating healthy exercise behaviours. * Allocate each of these strategies along the taxonomy of motivation, including amotivation, the four types of extrinsic motivation, and intrinsic motivation. '''Table 1'''. What Might Someone With Each of These Six Types of Motivation Say about Their Reasons for Exercising? {| class="wikitable" style="margin: auto;" ! Type !! Example reason |- | '''Amotivation''' | " ......... ? ......... " |- | '''External regulation''' | " ......... ? ......... " |- | '''Introjection''' | " ......... ? ......... " |- | '''Identification''' | " ......... ? ......... " |- | '''Integration''' | " ......... ? ......... " |- | '''Intrinsic motivation''' | " ......... ? ......... " |} For examples, see Table 2. ==Answers== '''Table 2'''. Examples of Reasons to Engage in Healthy Exercise Based on the Taxonomy of Motivation (Deci & Ryan, 2000) {| class="wikitable" style="margin: auto;" ! Type !! Example reason |- | '''Amotivation''' | "I don't see any point in exercising because it doesn't make a difference." |- | '''External regulation''' | "My doctor told me I have to exercise." |- | '''Introjection''' | "I feel guilty when I don't exercise." |- | '''Identification''' | "Being fit is important to me." |- | '''Integration''' | "Taking care of my body is part of who I am." |- | '''Intrinsic motivation''' | "I exercise because I genuinely enjoy being active." |} ==Topic development feedback== * '''Check your feedback and marks''' ** Check the marks on [[Motivation and emotion/Assessment/Topic|UCLearn]] ** For written feedback, consult: *** [[Motivation and emotion/Assessment/Topic/Feedback|Topic development - General feedback]] *** Topic-specific feedback on the topic's [[Motivation and emotion/Assessment/Topic|discussion (talk) page]] for written feedback ** Follow up if you do not understand the feedback * '''Align the topic structure''' ** Ensure clear alignments across '''title/sub-title → focus questions → headings''' ** Make sure each heading directly addresses the topic and contributes to answering the focus questions ** Avoid too much general background information: '''focus directly on the topic and cut to the chase''' * '''Balance theory and research''' ** Balance coverage of '''theory and research''', ideally integrating them rather than treating them as separate sections ** Identify and use the '''best psychological science on the topic''', particularly systematic reviews and/or meta-analyses ** Avoid relying too heavily on theory and too little on relevant empirical research * '''Embed links to related information''' ** As a learning feature, add relevant links on first mention of key words to: *** Other [[Motivation and emotion/Book|book chapters]] *** [[Wikipedia]] articles *** Other useful sources of information where appropriate * '''Acknowledge generative AI use''' ** Acknowledge use of generative AI in '''edit summaries''' by including a '''shared link to the ChatGPT conversation''' ** Follow the [[Motivation and emotion/Assessment/Using generative AI|using generative AI guidelines]] for academic honesty and transparency ===Messy middle=== We are now in the "messy middle" of the [[Motivation and emotion/Assessment/Chapter|book chapter]] development: * '''Motivational pattern''' (consistent with motivational science about the trajectory of motivation) ** Strong at '''start''' (excitement, newness) ** Strong at '''end''' (deadline pressure, completion goals) ** Dips in '''middle''' (novelty fades, finish feels long, distractions increase) * '''Strategies for the middle''' ** Make '''small, regular edits''' → steady progress ** Use '''scaffolding''' → build on [[Motivation and emotion/Assessment/Topic|topic development]] feedback and work towwards [[Motivation and emotion/Assessment/Chapter|chapter guidelines]] ** Seek clarification; follow up if unsure * '''Key idea''' ** Keep '''momentum''' alive in the “messy middle”—in this case, by doing small edits regularly to move from Topic Development → Book Chapter ==Recording== * [https://au-lti.bbcollab.com/recording/56e88f2f9a5a4977972c3adcf0b116fb Tutorial 4] (2026)<!-- * [https://au-lti.bbcollab.com/recording/fecbd3c2b9c94ee8bf7aaf6730226a53 Tutorial 4] (2025) * [https://au-lti.bbcollab.com/recording/9717613592cf458099da1b8e021fe13f Tutorial 4] (2024) * [https://au-lti.bbcollab.com/recording/5a95256f932d4e228992199adcb6c094 Tutorial 4] (2023) * [https://au-lti.bbcollab.com/recording/8eeaa7d6c18c4efbafc2c28984bfbaca Tutorial 4] (2022) * [https://au-lti.bbcollab.com/recording/ee193c24a6414276b3d47acba500d433 Tutorial 4] (2021) --> ==See also== * [[/Instructor notes/]] ;Additional tutorial material * [[/Example of self-determination theory: Child cleaning teeth/|Example of SDT: Child cleaning teeth]] * [[../Needs/Implicit motives/|Implicit motives]] * [[../Needs/Models which provide organisation of needs/|Models which organise needs]] * [[/Self-determination theory/]] <!-- ;Book chapters --> <!-- ;Wikipedia --> ; Lecture * [[Motivation and emotion/Lectures/Extrinsic motivation and psychological needs|Extrinsic motivation and psychological needs]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Physiological needs|Physiological needs]] (Previous tutorial) * [[Motivation and emotion/Tutorials/Functionalist theory and self-tracking|Functionalist theory and self-tracking]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1=Deci, R. M., & Ryan, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. ''Contemporary Educational Psychology'', ''25''(1), 54–67. https://doi.org/10.1006/ceps.1999.1020 [https://www.sciencedirect.com/science/article/pii/S0361476X99910202/pdf?md5=b9e2589a068cf7f9529c1bff165ddd55&pid=1-s2.0-S0361476X99910202-main.pdf PDF]}} ==External links== * [http://www.youtube.com/watch?v=VGrcets0E6I Promoting motivation, health, and excellence] (Ed Deci, 2012, TEDx, YouTube 14:05 mins) * [https://selfdeterminationtheory.org/ Self-determination theory] (selfdeterminationtheory.org) <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Psychological needs]] k0fxka5zyyml8wiomo3if5fgvo64wmy 0 299883 2835333 2759262 2026-10-01T12:18:22Z Username142857 2937508 2835333 wikitext text/x-wiki This resource will detail the 5 equations for motion under constant acceleration/deceleration. For the purposes of this resource, deceleration will be treated identically to acceleration in the opposite direction. Velocities are speeds with directions and displacements are distances with directions. == Constant Velocity == === 1d motion === == Constant acceleration == === 1d motion === There are two 'intuitive' equations: # [final velocity]=[initial velocity]+[acceleration][time elapsed] (<math>v_f=v_i+at</math>), or in other words, the final velocity is the sum of the initial and the product of the acceleration and elapsed time. This makes intuitive sense, for the final velocity is the sum of the initial velocity and the (signed) change in velocity (<math>v_f=v_i+\Delta v</math>). The (signed) change in velocity per unit time is the acceleration by definition (<math>a=\frac{\Delta v}{t}</math>). # [displacement]=(([initial velocity]+[final velocity])/2)[time elapsed] (<math>s=\frac{v_f+v_i}{2}t</math>), or in other words, the displacement is the product of the time elapsed and the mean of the initial and final velocities. This makes intuitive sense, for the initial velocity would give a number too low (if the final velocity is higher) or too high (if the final velocity is lower), and the final velocity would give a number too low (if the initial velocity is higher) or too high (if the initial velocity is lower). There are two, slightly less intuitive equations: # [displacement]=[initial velocity][time elapsed]+([acceleration][time elapsed]^2)/2 (<math>s=v_it+\frac{1}{2}at^2</math>), or in other words, the displacement is the sum of the product of the initial velocity and elapsed time and half the product of the acceleration and the square of the elapsed time. This is intuitive as the product of the final velocity and elapsed time is the sum of the product of the initial velocity and elapsed time and the product of the acceleration and the square of the elapsed time (<math>v_ft=v_it+at^2</math>) (recall that the final velocity is the sum of the initial and the product of the acceleration and elapsed time (<math>v_f=v_i+at</math>)), so the halving serves as a middle ground. # [displacement]=[final velocity][time elapsed]-([acceleration][time elapsed]^2)/2 (<math>s=v_ft-\frac{1}{2}at^2</math>), or in other words, the displacement is half the product of the acceleration and the square of the elapsed time subtracted from the product of the final velocity and elapsed time. This is intuitive as the product of the initial velocity and elapsed time is the product of the acceleration and the square of the elapsed time subtracted from the product of the final velocity and elapsed time (<math>v_it=v_ft-at^2</math>) (recall that since the final velocity is the sum of the initial and the product of the acceleration and elapsed time (<math>v_f=v_i+at</math>), the initial velocity is the product of the acceleration and elapsed time subtracted from the final velocity (<math>v_i=v_f-at</math>)), so the halving serves as a middle ground. There is one final equation that completely defies intuition: [final velocity]^2=[intitial velocity]^2+2[acceleration][displacement] (<math>v_f^2=v_i^2+2as</math>), or in other words, the square of the final velocity is the sum of the square of the initial velocity and twice the product of the acceleration and displacement. ==== Proof that they work ==== === Higher Dimensions === == Constant jerk == At this point, intuition must be abandoned in favour of mathematics === Displacement-independent Equations === There are five displacement-independent equations under constant jerk, inherited from the equations for constant acceleration. <math>a_f=a_i+jt</math>, <math>v_f-v_i=\frac{a_f+a_i}{2}t</math>, <math>v_f-v_i=a_it+\frac{1}{2}jt^2</math>, <math>v_f-v_i=a_ft-\frac{1}{2}jt^2</math>, and <math>a_f^2=a_i^2+2j(v_f-v_i)</math>. === Displacement-dependent Equations === Since <math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}jt^3</math> (derived from the Taylor series expansion), displacement-dependent equations assuming constant jerk must include four parameters (in this case, v_i, a_i, j, and t), giving fifteen different possible equations. Here's a table of equations: {| class="wikitable" |+ ! colspan="6" |Present? ! rowspan="2" |Formula ! rowspan="2" |Explanation |- !v_f !a_f !v_i !a_i !j !t |- |F |F |T |T |T |T |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}jt^3</math> |Taylor series expansion |- |F |T |F |T |T |T |n/a |Parameters aren't independent, since <math>a_f=a_i+jt</math> |- |F |T |T |F |T |T |<math>s=v_it+\frac{1}{2}a_ft^2-\frac{1}{3}jt^3</math> |Substituting a_i with <math>a_f-jt</math> |- |F |T |T |T |F |T |<math>s=v_it+(\frac{1}{3}a_i+\frac{1}{6}a_f)t^2</math> |Substituting j with <math>\frac{a_f-a_i}{t}</math> |- |F |T |T |T |T |F |<math>6j^2s=6v_ij(a_f-a_i)+(a_f+2a_i)(a_f-a_i)^2</math> |Substituting t with <math>\frac{a_f-a_i}{j}</math> |- |T |F |F |T |T |T |<math>s=v_ft-\frac{1}{2}a_it^2-\frac{1}{3}jt^3</math> |Substituting v_i with <math>v_f-a_it-\frac{1}{2}jt^2</math> |- |T |F |T |F |T |T |<math>s=\frac{v_f+v_i}{2}t-\frac{1}{12}jt^3</math> |Substituting a_i with <math>\frac{v_f-v_i}{t}-\frac{1}{2}jt</math> |- |T |F |T |T |F |T |<math>s=(\frac{2}{3}v_i+\frac{1}{3}v_f)t+\frac{1}{6}a_it^2</math> |Substituting j with <math>\frac{2(v_f-v_i-a_it)}{t^2}</math> |- |T |F |T |T |T |F |<math>9j^2s^2-6a_i(a_i^2-3jv_i)s=(v_f-v_i)(2j(v_f+2v_i)^2-3a_i^2(v_f+v_i))</math> |See below |- |T |T |F |F |T |T |<math>s=v_ft-\frac{1}{2}a_ft^2+\frac{1}{6}jt^3</math> |Substituting v_i with <math>v_f-a_it-\frac{1}{2}jt^2</math> and a_i with <math>a_f-jt</math> |- |T |T |F |T |F |T |<math>s=v_ft-(\frac{1}{6}a_i+\frac{1}{3}a_f)t^2</math> |Substituting v_i with <math>v_f-\frac{a_f+a_i}{2}t</math> and j with <math>\frac{a_f-a_i}{t}</math> |- |T |T |F |T |T |F |<math>6j^2s=6v_fj(a_f-a_i)-(2a_f+a_i)(a_f-a_i)^2</math> |Substituting v_i with <math>\frac{a_f^2-a_i^2}{2j}</math> and t with <math>\frac{a_f-a_i}{j}</math> |- |T |T |T |F |F |T |<math>s=(\frac{1}{3}v_i+\frac{2}{3}v_f)t-\frac{1}{6}a_ft^2</math> |Substituting a_i with <math>\frac{2(v_f-v_i)}{t}-a_f</math> and j with <math>\frac{2(a_ft-v_f+v_i)}{t^2}</math> |- |T |T |T |F |T |F |<math>9j^2s^2+6a_f(a_f^2-3jv_f)s=(v_f-v_i)(3a_f^2(v_f+v_i)-2j(2v_f+v_i)^2)</math> |See below |- |T |T |T |T |F |F |<math>\frac{3(a_f+a_i)^2s}{2(v_f-v_i)}=a_iv_i+2a_iv_f+2v_ia_f+a_fv_f</math> |Substituting j with <math>\frac{a_f^2-a_i^2}{2(v_f-v_i)}</math> and t with <math>\frac{2(v_f-v_i)}{a_f+a_i}</math> |} === Deriving the {v_f, v_i, a_i, j} equation === To derive the {v_f, v_i, a_i, j} equation, we could substitute t in <math>v_it+\frac{1}{2}a_it^2+\frac{1}{6}jt^3</math> by using the fact that <math>v_f-v_i=a_it+\frac{1}{2}jt^2</math>. However, we get two values of t and therefore, two values of s, showing that the equation must necessarily be a quadratic in s. Since <math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}jt^3</math>, <math>s^2=v_i^2t^2+v_ia_it^3+(\frac{1}{3}v_ij+\frac{1}{4}a_i^2)t^4+\frac{1}{6}a_ijt^5+\frac{1}{36}j^2t^6</math>, and, since the equation is time-independent, it must be a cubic in v_f-v_i. Since <math>v_f-v_i=a_it+\frac{1}{2}jt^2</math>, <math>(v_f-v_i)^2=a_i^2t^2+a_ijt^3+\frac{1}{4}j^2t^4</math>, and <math>(v_f-v_i)^3=a_i^3t^3+\frac{3}{2}a_i^2jt^4+\frac{3}{4}a_ij^2t^5+\frac{1}{8}j^3t^6</math>. Since <math>\frac{2}{9j}(v_f-v_i)^3=\frac{2}{9j}a_i^3t^3+\frac{1}{3}a_i^2t^4+\frac{1}{6}a_ijt^5+\frac{1}{36}j^2t^6</math>, <math>s^2-\frac{2}{9j}(v_f-v_i)^3=v_i^2t^2+(v_ia_i-\frac{2}{9j}a_i^3)t^3+(\frac{1}{3}v_ij-\frac{1}{12}a_i^2)t^4</math>. Since <math>(v_f-v_i)^2=a_i^2t^2+a_ijt^3+\frac{1}{4}j^2t^4</math>, <math>(\frac{4}{3j}v_i-\frac{1}{3j^2}a_i^2)(v_f-v_i)^2=(\frac{4}{3j}v_ia_i^2-\frac{1}{3j^2}a_i^4)t^2+(\frac{4}{3}v_ia_i-\frac{1}{3j}a_i^3)t^3+(\frac{1}{3}v_ij-\frac{1}{12}a_i^2)t^4</math>, and <math>s^2-\frac{2}{9j}(v_f-v_i)^3-(\frac{4}{3j}v_i-\frac{1}{3j^2}a_i^2)(v_f-v_i)^2=(v_i^2-\frac{4}{3j}v_ia_i^2+\frac{1}{3j^2}a_i^4)t^2+(\frac{1}{9j}a_i^3-\frac{1}{3}v_ia_i)t^3</math>. Since <math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}jt^3</math>, <math>(\frac{2}{3j^2}a_i^3-\frac{2}{j}v_ia_i)s=(\frac{2}{3j^2}v_ia_i^3-\frac{2}{j}v_i^2a_i)t+(\frac{1}{3j^2}a_i^4-\frac{1}{j}v_ia_i^2)t^2+(\frac{1}{9j}a_i^3-\frac{1}{3}v_ia_i)t^3</math>, and <math>s^2-\frac{2}{9j}(v_f-v_i)^3-(\frac{4}{3j}v_i-\frac{1}{3j^2}a_i^2)(v_f-v_i)^2-(\frac{2}{3j^2}a_i^3-\frac{2}{j}v_ia_i)s=(\frac{2}{j}v_i^2a_i-\frac{2}{3j^2}v_ia_i^3)t+(v_i^2-\frac{1}{3j}v_ia_i^2)t^2</math>, or, since <math>v_f-v_i=a_it+\frac{1}{2}jt^2</math>, <math>(\frac{2}{j}v_i^2-\frac{2}{3j^2}v_ia_i^2)(v_f-v_i)</math>. Therefore, <math>9j^2s^2-2j(v_f-v_i)^3-3(4jv_i-a_i^2)(v_f-v_i)^2-6(a_i^3-3jv_ia_i)s-6v_i(3jv_i-a_i^2)(v_f-v_i)=0</math>, and the equation above is true. A similar derivation exists for the {v_f, v_i, a_f, j} equation. == Constant snap == === Displacement-independent equations === There are 19 displacement-independent equations under constant snap, inherited from the equations for constant jerk, five of which are velocity-independent. <math>j_f=j_i+s_it</math>, <math>a_f-a_i=\frac{j_f+j_i}{2}t</math>, <math>a_f-a_i=j_it+\frac{1}{2}s_it^2</math>, <math>a_f-a_i=j_ft-\frac{1}{2}s_it^2</math>, and <math>j_f^2=j_i^2+2s_i(a_f-a_i)</math>. {| class="wikitable" |+ ! colspan="6" |Present? ! rowspan="2" |Formula |- !a_f !j_f !a_i !j_i !s_i !t |- |F |F |T |T |T |T |<math>v_f-v_i=a_it+\frac{1}{2}j_it^2+\frac{1}{6}s_it^3</math> |- |F |T |F |T |T |T |n/a |- |F |T |T |F |T |T |<math>v_f-v_i=a_it+\frac{1}{2}j_ft^2-\frac{1}{3}s_it^3</math> |- |F |T |T |T |F |T |<math>v_f-v_i=a_it+(\frac{1}{3}j_i+\frac{1}{6}j_f)t^2</math> |- |F |T |T |T |T |F |<math>6s_i^2(v_f-v_i)=6a_is_i(j_f-j_i)+(j_f+2j_i)(j_f-j_i)^2</math> |- |T |F |F |T |T |T |<math>v_f-v_i=a_ft-\frac{1}{2}j_it^2-\frac{1}{3}s_it^3</math> |- |T |F |T |F |T |T |<math>v_f-v_i=\frac{a_f+a_i}{2}t-\frac{1}{12}s_it^3</math> |- |T |F |T |T |F |T |<math>v_f-v_i=(\frac{2}{3}a_i+\frac{1}{3}a_f)t+\frac{1}{6}j_it^2</math> |- |T |F |T |T |T |F |<math>9s_i^2(v_f-v_i)^2-6j_i(j_i^2-3s_ia_i)(v_f-v_i)=(a_f-a_i)(2s_i(a_f+2a_i)^2-3j_i^2(a_f+a_i))</math> |- |T |T |F |F |T |T |<math>v_f-v_i=a_ft-\frac{1}{2}j_ft^2+\frac{1}{6}s_it^3</math> |- |T |T |F |T |F |T |<math>v_f-v_i=a_ft-(\frac{1}{6}j_i+\frac{1}{3}j_f)t^2</math> |- |T |T |F |T |T |F |<math>6s_i^2(v_f-v_i)=6a_fs_i(j_f-j_i)-(2j_f+j_i)(j_f-j_i)^2</math> |- |T |T |T |F |F |T |<math>v_f-v_i=(\frac{1}{3}a_i+\frac{2}{3}a_f)t-\frac{1}{6}j_ft^2</math> |- |T |T |T |F |T |F |<math>9s_i^2(v_f-v_i)^2+6j_f(j_f^2-3s_ia_f)(v_f-v_i)=(a_f-a_i)(3j_f^2(a_f+a_i)-2s_i(2a_f+a_i)^2)</math> |- |T |T |T |T |F |F |<math>\frac{3(j_f+j_i)^2(v_f-v_i)}{2(a_f-a_i)}=j_ia_i+2j_ia_f+2a_ij_f+j_fa_f</math> |} === Displacement-dependent equations === Since <math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+\frac{1}{24}s_it^4</math> (derived from the Taylor series expansion), displacement-dependent equations assuming constant snap must include five parameters (in this case, v_i, a_i, j_i, s_i, and t), giving 56 different possible equations. Here's a table of equations: {| class="wikitable" ! colspan="8" |Present? ! rowspan="2" |Formula ! rowspan="2" |Explanation |- !v_f !a_f !j_f !v_i !a_i !j_i !s_i !t |- |F |F |F |T |T |T |T |T |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+\frac{1}{24}s_it^4</math> |Taylor series expansion |- |F |F |T |F |T |T |T |T |n/a |Parameters aren't independent, since <math>j_f=j_i+s_it</math> |- |F |F |T |T |F |T |T |T |n/a |Parameters aren't independent, since <math>j_f=j_i+s_it</math> |- |F |F |T |T |T |F |T |T |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_ft^3-\frac{1}{8}s_it^4</math> |Substituting j_i with <math>j_f-s_it</math> |- |F |F |T |T |T |T |F |T |<math>s=v_it+\frac{1}{2}a_it^2+(\frac{1}{8}j_i+\frac{1}{24}j_f)t^3</math> |Substituting s_i with <math>\frac{j_f-j_i}{t}</math> |- |F |F |T |T |T |T |T |F |<math>24s_i^3s=24v_is_i^2(j_f-j_i)+12a_is_i(j_f-j_i)^2+(j_f+3j_i)(j_f-j_i)^3</math> |Substituting t with <math>\frac{j_f-j_i}{s_i}</math> |- |F |T |F |F |T |T |T |T |n/a |Parameters aren't independent, since <math>a_f-a_i=j_it+\frac{1}{2}s_it^2</math> |- |F |T |F |T |F |T |T |T |<math>s=v_it+\frac{1}{2}a_ft^2-\frac{1}{3}j_it^3-\frac{5}{24}s_it^4</math> |Substituting a_i with <math>a_f-j_it-\frac{1}{2}s_it^2</math> |- |F |T |F |T |T |F |T |T |<math>s=v_it+(\frac{1}{3}a_i+\frac{1}{6}a_f)t^2-\frac{1}{24}s_it^4</math> |Substituting j_i with <math>\frac{a_f-a_i}{t}-\frac{1}{2}s_it</math> |- |F |T |F |T |T |T |F |T |<math>s=v_it+(\frac{5}{12}a_i+\frac{1}{12}a_f)t^2+\frac{1}{12}j_it^3</math> |Substituting s_i with <math>\frac{2(a_f-a_i-j_it)}{t^2}</math> |- |F |T |F |T |T |T |T |F |<math>36s^2s_i^3-12s(a_f+5a_i)(a_f-a_i)s_i^2+(a_f+5a_i)^2(a_f-a_i)^2s_i+24s(a_f-3a_i)j_i^2s_i-4(a_f+2a_i)(a_f-a_i)^2j_i^2-12v_i(a_f-8a_i)(a_f-a_i)j_is_i=24(j_i^3+3v_is_i^2)(v_i(a_f-a_i)-j_is) </math> | |- |F |T |T |F |F |T |T |T |n/a |Parameters aren't independent, since <math>j_f=j_i+s_it</math> |- |F |T |T |F |T |F |T |T |n/a |Parameters aren't independent, since <math>a_f-a_i=j_ft-\frac{1}{2}s_it^2</math> |- |F |T |T |F |T |T |F |T |n/a |Parameters aren't independent, since <math>a_f-a_i=\frac{j_f+j_i}{2}t</math> |- |F |T |T |F |T |T |T |F |n/a |Parameters aren't independent, since <math>j_f^2=j_i^2+2s_i(a_f-a_i)</math> |- |F |T |T |T |F |F |T |T |<math>s=v_it+\frac{1}{2}a_ft^2-\frac{1}{3}j_ft^3+\frac{1}{8}s_it^4</math> |Substituting a_i with <math>a_f-j_ft+\frac{1}{2}s_it^2</math> and j_i with <math>j_f-s_it</math> |- |F |T |T |T |F |T |F |T |<math>s=v_it+\frac{1}{2}a_ft^2-(\frac{1}{8}j_i+\frac{5}{24}j_f)t^3</math> |Substituting a_i with <math>a_f-\frac{j_f+j_i}{2}t</math> and s_i with <math>\frac{j_f-j_i}{t}</math> |- |F |T |T |T |F |T |T |F |<math>24s_i^3s=24v_is_i^2(j_f-j_i)+12a_fs_i(j_f-j_i)^2-(5j_f+3j_i)(j_f-j_i)^3</math> |Substituting a_i with <math>a_f-\frac{j_f^2-j_i^2}{2s_i}</math> and t with <math>\frac{j_f-j_i}{s_i}</math> |- |F |T |T |T |T |F |F |T |<math>s=v_it+\frac{a_f+a_i}{4}t^2-\frac{1}{12}j_ft^3</math> |Substituting j_i with <math>\frac{2(a_f-a_i)}{t}-j_f</math> and s_i with <math>\frac{2(j_ft-a_f+a_i)}{t^2}</math> |- |F |T |T |T |T |F |T |F | | |- |F |T |T |T |T |T |F |F |<math>\frac{3s(j_f+j_i)^3}{a_f-a_i}=6v_i(j_f+j_i)^2+(a_i(5j_f+3j_i)+a_f(j_f+3j_i))(a_f-a_i)</math> |Substituting s_i with <math>\frac{j_f^2-j_i^2}{2(a_f-a_i)}</math> and t with <math>\frac{2(a_f-a_i)}{j_f+j_i}</math> |- |T |F |F |F |T |T |T |T |<math>s=v_ft-\frac{1}{2}a_it^2-\frac{1}{3}j_it^3-\frac{1}{8}s_it^4</math> |Substituting v_i with <math>v_f-a_it-\frac{1}{2}j_it^2-\frac{1}{6}s_it^3</math> |- |T |F |F |T |F |T |T |T |<math>s=\frac{v_f+v_i}{2}t-\frac{1}{12}j_it^3-\frac{1}{24}s_it^4</math> |Substituting a_i with <math>\frac{v_f-v_i}{t}-\frac{1}{2}j_it-\frac{1}{6}s_it^2</math> |- |T |F |F |T |T |F |T |T |<math>s=(\frac{2}{3}v_i+\frac{1}{3}v_f)t+\frac{1}{6}a_it^2-\frac{1}{72}s_it^4</math> |Substituting j_i with <math>\frac{2(v_f-v_i-a_it)}{t^2}-\frac{1}{3}s_it</math> |- |T |F |F |T |T |T |F |T |<math>s=(\frac{3}{4}v_i+\frac{1}{4}v_f)t+\frac{1}{4}a_it^2+\frac{1}{24}j_it^3</math> |Substituting s_i with <math>\frac{6(v_f-v_i-a_it)-3j_it^2}{t^3}</math> |- |T |F |F |T |T |T |T |F | | |- |T |F |T |F |F |T |T |T |n/a |Parameters aren't independent, since <math>j_f=j_i+s_it</math> |- |T |F |T |F |T |F |T |T |<math>s=v_ft-\frac{1}{2}a_it^2-\frac{1}{3}j_ft^3+\frac{5}{24}s_it^4</math> |Substituting v_i with <math>v_f-a_it-\frac{1}{2}j_ft^2+\frac{1}{3}s_it^3</math> and j_i with <math>j_f-s_it</math> |- |T |F |T |F |T |T |F |T |<math>s=v_ft-\frac{1}{2}a_it^2-(\frac{5}{24}j_i+\frac{1}{8}j_f)t^3</math> |Substituting v_i with <math>v_f-a_it-(\frac{1}{3}j_i+\frac{1}{6}j_f)t^2</math> and s_i with <math>\frac{j_f-j_i}{t}</math> |- |T |F |T |F |T |T |T |F |<math>24s_i^3s=24v_fs_i^2(j_f-j_i)-12a_is_i(j_f-j_i)^2-(3j_f+5j_i)(j_f-j_i)^3</math> |Substituting v_i with <math>v_f-\frac{6a_is_i(j_f-j_i)+(j_f+2j_i)(j_f-j_i)^2}{6s_i^2}</math> and t with <math>\frac{j_f-j_i}{s_i}</math> |- |T |F |T |T |F |F |T |T |<math>s=\frac{v_f+v_i}{2}t-\frac{1}{12}j_ft^3+\frac{1}{24}s_it^4</math> |Substituting a_i with <math>\frac{v_f-v_i}{t}-\frac{1}{2}j_ft+\frac{1}{3}s_it^2</math> and j_i with <math>j_f-s_it</math> |- |T |F |T |T |F |T |F |T |<math>s=\frac{v_f+v_i}{2}t-\frac{j_f+j_i}{24}t^3</math> |Substituting a_i with <math>\frac{v_f-v_i}{t}-(\frac{1}{3}j_i+\frac{1}{6}j_f)t</math> and s_i with <math>\frac{j_f-j_i}{t}</math> |- |T |F |T |T |F |T |T |F |<math>24s_i^3s=12s_i^2(v_f+v_i)(j_f-j_i)-(j_f+j_i)(j_f-j_i)^3</math> |Substituting a_i with <math>\frac{s_i(v_f-v_i)}{j_f-j_i}-\frac{(j_f+2j_i)(j_f-j_i)}{6s_i}</math> and t with <math>\frac{j_f-j_i}{s_i}</math> |- |T |F |T |T |T |F |F |T |<math>s=(\frac{5}{8}v_i+\frac{3}{8}v_f)t+\frac{1}{8}a_it^2-\frac{1}{48}j_ft^3</math> |Substituting j_i with <math>\frac{3(v_f-v_i-a_it)}{t^2}-\frac{1}{2}j_f</math> and s_i with <math>\frac{3(v_i-v_f+a_it+\frac{1}{2}j_ft^2)}{t^3}</math> |- |T |F |T |T |T |F |T |F | | |- |T |F |T |T |T |T |F |F | | |- |T |T |F |F |F |T |T |T |<math>s=v_ft-\frac{1}{2}a_ft^2+\frac{1}{6}j_it^3+\frac{1}{8}s_it^4</math> |Substituting a_i with <math>\frac{2(v_f-v_i)}{t}+\frac{1}{6}s_it^2-a_f</math> |- |T |T |F |F |T |F |T |T |<math>s=v_ft-(\frac{1}{6}a_i+\frac{1}{3}a_f)t^2+\frac{1}{24}s_it^4</math> |Substituting v_i with <math>v_f-\frac{a_f+a_i}{2}t+\frac{1}{12}s_it^3</math> and j_i with <math>\frac{a_f-a_i}{t}-\frac{1}{2}s_it</math> |- |T |T |F |F |T |T |F |T |<math>s=v_ft-\frac{a_f+a_i}{4}t^2-\frac{1}{12}j_it^3</math> |Substituting v_i with <math>v_f-(\frac{2}{3}a_i+\frac{1}{3}a_f)t-\frac{1}{6}j_it^2</math> and s_i with <math>\frac{2(a_f-a_i-j_it)}{t^2}</math> |- |T |T |F |F |T |T |T |F | | |- |T |T |F |T |F |F |T |T |<math>s=(\frac{1}{3}v_i+\frac{2}{3}v_f)t-\frac{1}{6}a_ft^2+\frac{1}{72}s_it^4</math> |Substituting a_i with <math>\frac{2(v_f-v_i)}{t}+\frac{1}{6}s_it^2-a_f</math> and j_i with <math>\frac{2(v_i-v_f+a_ft)}{t^2}-\frac{2}{3}s_it</math> |- |T |T |F |T |F |T |F |T |<math>s=(\frac{3}{8}v_i+\frac{5}{8}v_f)t-\frac{1}{8}a_ft^2-\frac{1}{48}j_it^3</math> |Substituting a_i with <math>\frac{3(v_f-v_i)}{2t}-\frac{1}{2}a_f-\frac{1}{4}j_it</math> and s_i with <math>\frac{3(v_i-v_f+a_ft-\frac{1}{2}j_it^2)}{t^3}</math> |- |T |T |F |T |F |T |T |F | | |- |T |T |F |T |T |F |F |T |<math>s=(\frac{4}{3}v_i-\frac{1}{3}v_f)t-\frac{a_f-a_i}{12}t^2</math> |Substituting j_i with <math>\frac{v_f-v_i-(4a_i+2a_f)t}{t^2}</math> and s_i with <math>\frac{12(v_i-v_f)+6(a_f+a_i)t}{t^3}</math>, |- |T |T |F |T |T |F |T |F | | |- |T |T |F |T |T |T |F |F | | |- |T |T |T |F |F |F |T |T |<math>s=v_ft-\frac{1}{2}a_ft^2+\frac{1}{6}j_ft^3-\frac{1}{24}s_it^4</math> |Substituting v_i with <math>v_f-a_ft+\frac{1}{2}j_ft^2-\frac{1}{6}s_it^3</math>, a_i with <math>a_f-j_ft+\frac{1}{2}s_it^2</math>, and j_i with <math>j_f-s_it</math> |- |T |T |T |F |F |T |F |T |<math>s=v_ft-\frac{1}{2}a_ft^2+(\frac{1}{24}j_i+\frac{1}{8}j_f)t^3</math> |Substituting v_i with <math>v_f-a_ft+(\frac{1}{6}j_i+\frac{1}{3}j_f)t^2</math>, a_i with <math>a_f-\frac{j_f+j_i}{2}t</math>, and s_i with <math>\frac{j_f-j_i}{t}</math> |- |T |T |T |F |F |T |T |F |<math>24s_i^3s=24v_fs_i^2(j_f-j_i)-12a_fs_i(j_f-j_i)^2+(3j_f+j_i)(j_f-j_i)^3</math> |Substituting v_i with <math>v_f-\frac{6a_fs_i(j_f-j_i)-(2j_f+j_i)(j_f-j_i)^2}{6s_i^2}</math>, a_i with <math>a_f-\frac{j_f^2-j_i^2}{2s_i}</math>, and t with <math>\frac{j_f-j_i}{s_i}</math> |- |T |T |T |F |T |F |F |T |<math>s=v_ft-(\frac{1}{12}a_i+\frac{5}{12}a_f)t^2+\frac{1}{12}j_ft^3</math> |Substituting v_i with <math>v_f-(\frac{1}{3}a_i+\frac{2}{3}a_f)t+\frac{1}{6}j_ft^2</math>, j_i with <math>\frac{2(a_f-a_i)}{t}-j_f</math>, and s_i with <math>\frac{2(a_i-a_f+j_ft)}{t^2}</math> |- |T |T |T |F |T |F |T |F | | |- |T |T |T |F |T |T |F |F |<math>\frac{3s(j_f+j_i)^3}{a_f-a_i}=6v_f(j_f+j_i)^2-(a_i(3j_f+j_i)+a_f(3j_f+5j_i))(a_f-a_i)</math> |Substituting v_i with <math>v_f-\frac{2(a_f-a_i)}{3(j_f+j_i)^2}(j_ia_i+2j_ia_f+2a_ij_f+j_fa_f)</math>, s_i with <math>\frac{j_f^2-j_i^2}{2(a_f-a_i)}</math>, and t with <math>\frac{2(a_f-a_i)}{j_f+j_i}</math> |- |T |T |T |T |F |F |F |T |<math>s=(\frac{1}{4}v_i+\frac{3}{4}v_f)t-\frac{1}{4}a_ft^2+\frac{1}{24}j_ft^3</math> |Substituting a_i with <math>\frac{3(v_f-v_i)}{t}-2a_f+\frac{1}{2}j_ft</math>, j_i with <math>\frac{6(v_i-v_f+a_ft)}{t^2}-2j_f</math>, and s_i with <math>\frac{6(v_f-v_i-a_ft)+3j_ft^2}{t^3}</math> |- |T |T |T |T |F |F |T |F | | |- |T |T |T |T |F |T |F |F | | |- |T |T |T |T |T |F |F |F | | |} === Deriving the {a_f, v_i, a_i, j_i, s_i} equation === To derive the {a_f, v_i, a_i, j_i, s_i} equation, we could substitute t in <math>v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+\frac{1}{24}s_it^4</math> by using the fact that <math>a_f-a_i=j_it+\frac{1}{2}s_it^2</math>. However, we get two values of t and therefore, two values of s, showing that the equation must necessarily be a quadratic in s. Since <math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+\frac{1}{24}s_it^4</math>, <math>s^2=v_i^2t^2+v_ia_it^3+(\frac{1}{3}v_ij_i+\frac{1}{4}a_i^2)t^4+(\frac{1}{6}a_ij_i+\frac{1}{12}v_is_i)t^5+(\frac{1}{36}j_i^2+\frac{1}{24}a_is_i)t^6+\frac{1}{72}j_is_it^7+\frac{1}{576}s_i^2t^8</math>, and, since the equation is time-independent, it must be a quartic in a_f-a_i. Since <math>a_f-a_i=j_it+\frac{1}{2}s_it^2</math>, <math>(a_f-a_i)^2=j_i^2t^2+j_is_it^3+\frac{1}{4}s_i^2t^4</math>, <math>(a_f-a_i)^3=j_i^3t^3+\frac{3}{2}j_i^2s_it^4+\frac{3}{4}j_is_i^2t^5+\frac{1}{8}s_i^3t^6</math>, and <math>(a_f-a_i)^4=j_i^4t^4+2j_i^3s_it^5+\frac{3}{2}j_i^2s_i^2t^6+\frac{1}{2}j_is_i^3t^7+\frac{1}{16}s_i^4t^8</math>. We may also conclude that <math>s(a_f-a_i)=v_ij_it^2+\frac{1}{2}(v_is_i+a_ij_i)t^3+(\frac{1}{6}j_i^2+\frac{1}{4}a_is_i)t^4+\frac{1}{8}j_is_it^5+\frac{1}{48}s_i^2t^6</math> and <math>s(a_f-a_i)^2=v_ij_i^2t^3+(v_ij_is_i+\frac{1}{2}a_ij_i^2)t^4+(\frac{1}{4}v_is_i^2+\frac{1}{2}a_ij_is_i+\frac{1}{6}j_i^3)t^5+(\frac{1}{8}a_is_i^2+\frac{5}{24}j_i^2s_i)t^6+\frac{1}{12}j_is_i^2t^7+\frac{1}{96}s_i^3t^8</math>. Note that all but one of these equations can be paired based on degree, and the ratio between the two leading terms is fixed for each pair: {| class="wikitable" |+ !Degree !Equation(s) !<math>\frac{leading\ coefficient}{second\ leading\ coefficient}</math> |- |8 |<math>s(a_f-a_i)^2=O(t^6)+\frac{1}{12}j_is_i^2t^7+\frac{1}{96}s_i^3t^8</math><math>(a_f-a_i)^4=j_i^4t^4+2j_i^3s_it^5+\frac{3}{2}j_i^2s_i^2t^6+\frac{1}{2}j_is_i^3t^7+\frac{1}{16}s_i^4t^8</math> |<math>\frac{s_i}{8j_i}</math> |- |6 |<math>s(a_f-a_i)=v_ij_it^2+\frac{1}{2}(v_is_i+a_ij_i)t^3+(\frac{1}{6}j_i^2+\frac{1}{4}a_is_i)t^4+\frac{1}{8}j_is_it^5+\frac{1}{48}s_i^2t^6</math><math>(a_f-a_i)^3=j_i^3t^3+\frac{3}{2}j_i^2s_it^4+\frac{3}{4}j_is_i^2t^5+\frac{1}{8}s_i^3t^6</math> |<math>\frac{s_i}{6j_i}</math> |- |4 |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+\frac{1}{24}s_it^4</math><math>(a_f-a_i)^2=j_i^2t^2+j_is_it^3+\frac{1}{4}s_i^2t^4</math> |<math>\frac{s_i}{4j_i}</math> |- |2 |<math>a_f-a_i=j_it+\frac{1}{2}s_it^2</math> |<math>\frac{s_i}{2j_i}</math> |} The message is clear: subtract higher degree polynomials to cancel out higher powers of t such that the lower degrees inherit the correct ratio. ==== Degree-8 polynomials ==== Since <math>\frac{s(a_f-a_i)^2}{s_i}=O(t^4)+(\frac{1}{4}v_is_i+\frac{1}{2}a_ij_i+\frac{1}{6s_i}j_i^3)t^5+(\frac{1}{8}a_is_i+\frac{5}{24}j_i^2)t^6+\frac{1}{12}j_is_it^7+\frac{1}{96}s_i^2t^8</math> and <math>\frac{(a_f-a_i)^4}{s_i^2}=O(t^4)+\frac{2}{s_i}j_i^3t^5+\frac{3}{2}j_i^2t^6+\frac{1}{2}j_is_it^7+\frac{1}{16}s_i^2t^8</math>, <math>\forall r\ r\frac{s(a_f-a_i)^2}{s_i}+(\frac{1}{36}-\frac{r}{6})\frac{(a_f-a_i)^4}{s_i^2}=O(t^4)+(\frac{r}{4}v_is_i+\frac{r}{2}a_ij_i+\frac{1-3r}{18s_i}j_i^3)t^5+(\frac{r}{8}a_is_i+\frac{1-r}{24}j_i^2)t^6+\frac{1}{72}j_is_it^7+\frac{1}{576}s_i^2t^8 </math>and <math>\forall r\ s^2-r\frac{s(a_f-a_i)^2}{s_i}+(\frac{r}{6}-\frac{1}{36})\frac{(a_f-a_i)^4}{s_i^2}=O(t^4)+(\frac{1-3r}{12}v_is_i+\frac{1-3r}{6}a_ij_i+\frac{3r-1}{18s_i}j_i^3)t^5+(\frac{1-3r}{24}a_is_i+\frac{3r-1}{72}j_i^2)t^6 </math>. Since we know that we want <math>\frac{1-3r}{24}a_is_i+\frac{3r-1}{72}j_i^2</math> to equal <math>\frac{s_i}{6j_i}(\frac{1-3r}{12}v_is_i+\frac{1-3r}{6}a_ij_i+\frac{3r-1}{18s_i}j_i^3)</math>, it's clear that r must equal <math>\frac{1}{3}</math>, and we consider that <math>s^2-\frac{s(a_f-a_i)^2}{3s_i}+\frac{(a_f-a_i)^4}{36s_i^2}=v_i^2t^2+(v_ia_i-\frac{1}{3s_i}v_ij_i^2)t^3+(\frac{1}{4}a_i^2-\frac{1}{6s_i}a_ij_i^2+\frac{1}{36s_i^2}j_i^4)t^4 </math>. ==== Degree-6 polynomials ==== Since <math>\frac{a_is(a_f-a_i)}{s_i}=\frac{1}{s_i}v_ia_ij_it^2+(\frac{1}{2}v_ia_i+\frac{1}{2s_i}a_i^2j_i)t^3+(\frac{1}{6s_i}a_ij_i^2+\frac{1}{4}a_i^2)t^4+\frac{1}{8}a_ij_it^5+\frac{1}{48}a_is_it^6</math> and <math>\frac{a_i(a_f-a_i)^3}{s_i^2}=\frac{1}{s_i^2}a_ij_i^3t^3+\frac{3}{2s_i}a_ij_i^2t^4+\frac{3}{4}a_ij_it^5+\frac{1}{8}a_is_it^6</math>, <math>\forall r\ r\frac{a_is(a_f-a_i)}{s_i}-\frac{r}{6}\frac{a_i(a_f-a_i)^3}{s_i^2}=\frac{r}{s_i}v_ia_ij_it^2+(\frac{r}{2}v_ia_i+\frac{r}{2s_i}a_i^2j_i-\frac{r}{6s_i^2}a_ij_i^3)t^3+(\frac{r}{4}a_i^2-\frac{r}{12s_i}a_ij_i^2)t^4 </math> and <math>\forall r\ s^2-\frac{s(a_f-a_i)^2}{3s_i}+\frac{(a_f-a_i)^4}{36s_i^2}-r\frac{a_is(a_f-a_i)}{s_i}+\frac{r}{6}\frac{a_i(a_f-a_i)^3}{s_i^2}=(v_i^2-\frac{r}{s_i}v_ia_ij_i)t^2+(\frac{2-r}{2}v_ia_i-\frac{1}{3s_i}v_ij_i^2-\frac{r}{2s_i}a_i^2j_i+\frac{r}{6s_i^2}a_ij_i^3)t^3+(\frac{1-r}{4}a_i^2+\frac{r-2}{12s_i}a_ij_i^2+\frac{1}{36s_i^2}j_i^4)t^4 </math>Since we know that we want <math>\frac{1-r}{4}a_i^2+\frac{r-2}{12s_i}a_ij_i^2+\frac{1}{36s_i^2}j_i^4</math> to equal <math>\frac{s_i}{4j_i}(\frac{2-r}{2}v_ia_i-\frac{1}{3s_i}v_ij_i^2-\frac{r}{2s_i}a_i^2j_i+\frac{r}{6s_i^2}j_i^3)</math>, the former doesn't depend on v_i and the latter does, we can guess that r should be such that v_i has no contribution. If <math>\frac{2-r}{2}a_i=\frac{1}{3s_i}j_i^2</math>, then <math>r=2-\frac{2}{3a_is_i}j_i^2</math>, <math>\frac{1-r}{4}a_i^2+\frac{r-2}{12s_i}a_ij_i^2+\frac{1}{36s_i^2}j_i^4=\frac{1}{6s_i}a_ij_i^2-\frac{1}{4}a_i^2-\frac{1}{36s_i^2}j_i^4</math> and <math>\frac{s_i}{4j_i}(\frac{2-r}{2}v_ia_i-\frac{1}{3s_i}v_ij_i^2-\frac{r}{2s_i}a_i^2j_i+\frac{r}{6s_i^2}a_ij_i^3)=\frac{1}{6s_i}a_ij^2-\frac{1}{4}a_i^2-\frac{1}{36s_i^2}j_i^4</math>, making them both equal. We will consider that <math>s^2-\frac{s(a_f-a_i)^2}{3s_i}+\frac{(a_f-a_i)^4}{36s_i^2}+(\frac{2}{3a_is_i}j_i^2-2)\frac{a_is(a_f-a_i)}{s_i}+(\frac{1}{3}-\frac{1}{9a_is_i}j_i^2)\frac{a_i(a_f-a_i)^3}{s_i^2}=(v_i^2-\frac{2}{s_i}v_ia_ij_i+\frac{2}{3s_i^2}v_ij_i^3)t^2+(\frac{2}{3s_i^2}a_ij_i^3-\frac{1}{s_i}a_i^2j_i-\frac{1}{9s_i^3}j_i^5)t^3+(\frac{1}{6s_i}a_ij_i^2-\frac{1}{4}a_i^2-\frac{1}{36s_i^2}j_i^4)t^4 </math>. ==== Degree-4 polynomials ==== Since <math>\frac{a_i^2s}{s_i}=\frac{1}{s_i}v_ia_i^2t+\frac{1}{2s_i}a_i^3t^2+\frac{1}{6s_i}a_i^2j_it^3+\frac{1}{24}a_i^2t^4</math> and <math>\frac{a_i^2(a_f-a_i)^2}{s_i^2}=\frac{1}{s_i^2}a_i^2j_i^2t^2+\frac{1}{s_i}a_i^2j_it^3+\frac{1}{4}a_i^2t^4</math>, <math>\forall r\ r\frac{a_i^2s}{s_i}+(\frac{2}{3a_is_i}j_i^2-\frac{6+r}{6}-\frac{1}{9a_i^2s_i^2}j_i^4)\frac{a_i^2(a_f-a_i)^2}{s_i^2}=\frac{r}{s_i}v_ia_i^2t+(\frac{r}{2s_i}a_i^3+\frac{2}{3s_i^3}a_ij_i^4-\frac{6+r}{6s_i^2}a_i^2j_i^2-\frac{1}{9s_i^4}j_i^6)t^2+(\frac{2}{3s_i^2}a_ij_i^3-\frac{1}{s_i}a_i^2j_i-\frac{1}{9s_i}j_i^5)t^3+(\frac{1}{6s_i}a_ij_i^2-\frac{1}{4}a_i^2-\frac{1}{36s_i^2}j_i^4)t^4</math> and <math>s^2-\frac{s(a_f-a_i)^2}{3s_i}+\frac{(a_f-a_i)^4}{36s_i^2}+(\frac{2}{3a_is_i}j_i^2-2)\frac{a_is(a_f-a_i)}{s_i}+(\frac{1}{3}-\frac{1}{9a_is_i}j_i^2)\frac{a_i(a_f-a_i)^3}{s_i^2}-r\frac{a_i^2s}{s_i}-(\frac{2}{3a_is_i}j_i^2-\frac{6+r}{6}-\frac{1}{9a_i^2s_i^2}j_i^4)\frac{a_i^2(a_f-a_i)^2}{s_i^2}=-\frac{r}{s_i}v_ia_i^2t+(v_i^2-\frac{2}{s_i}v_ia_ij_i+\frac{2}{3s_i^2}v_ij_i^3-\frac{r}{2s_i}a_i^3-\frac{2}{3s_i^3}a_ij_i^4+\frac{6+r}{6s_i^2}a_i^2j_i^2+\frac{1}{9s_i^4}j_i^6)t^2 </math>Since we know that we want <math>v_i^2-\frac{2}{s_i}v_ia_ij_i+\frac{2}{3s_i^2}v_ij_i^3-\frac{r}{2s_i}a_i^3-\frac{2}{3s_i^3}a_ij_i^4+\frac{6+r}{6s_i^2}a_i^2j_i^2+\frac{1}{9s_i^4}j_i^6</math> to equal <math>-\frac{s_i}{2j_i}\frac{r}{s_i}v_ia_i^2</math>, we may determine what r should be. <math>v_i^2-\frac{2}{s_i}v_ia_ij_i+\frac{2}{3s_i^2}v_ij_i^3-\frac{r}{2s_i}a_i^3-\frac{2}{3s_i^3}a_ij_i^4+\frac{6+r}{6s_i^2}a_i^2j_i^2+\frac{1}{9s_i^4}j_i^6=-\frac{s_i}{2j_i}\frac{r}{s_i}v_ia_i^2</math> <math>v_i^2-\frac{2}{s_i}v_ia_ij_i+\frac{2}{3s_i^2}v_ij_i^3-\frac{r}{2s_i}a_i^3-\frac{2}{3s_i^3}a_ij_i^4+\frac{1}{s_i^2}a_i^2j_i^2+\frac{r}{6s_i^2}a_i^2j_i^2+\frac{1}{9s_i^4}j_i^6=-\frac{r}{2j_i}v_ia_i^2</math> <math>v_i^2-\frac{2}{s_i}v_ia_ij_i+\frac{2}{3s_i^2}v_ij_i^3-\frac{2}{3s_i^3}a_ij_i^4+\frac{1}{s_i^2}a_i^2j_i^2+\frac{1}{9s_i^4}j_i^6=\frac{r}{2s_i}a_i^3-\frac{r}{2j_i}v_ia_i^2-\frac{r}{6s_i^2}a_i^2j_i^2</math> <math>18v_i^2j_is_i^4-36v_ia_ij_i^2s_i^3+12v_ij_i^4s_i^2-12a_ij_i^5s_i+18a_i^2j_i^3s_i^2+2j_i^7=r(9a_i^3j_is_i^3-9v_ia_i^2s_i^4-3a_i^2j_i^3s_i^2)</math> <math>r=\frac{2j_i}{3}\frac{9v_i^2s_i^4-18v_ia_ij_is_i^3+6v_ij_i^3s_i^2-6a_ij_i^4s_i+9a_i^2j_i^2s_i^2+j_i^6}{3a_i^3j_is_i^3-3v_ia_i^2s_i^4-a_i^2j_i^3s_i^2}=-\frac{2j_i}{3}(\frac{1}{a_i^2s_i^2}j_i^3-\frac{3}{a_is_i}j_i+\frac{3v_i}{a_i^2})=-\frac{2j_i}{3a_i^2s_i^2}(j_i^3-3a_is_ij_i+3v_is_i^2)</math>We will now consider that <math>s^2-\frac{s(a_f-a_i)^2}{3s_i}+\frac{(a_f-a_i)^4}{36s_i^2}+(\frac{2}{3a_is_i}j_i^2-2)\frac{a_is(a_f-a_i)}{s_i}+(\frac{1}{3}-\frac{1}{9a_is_i}j_i^2)\frac{a_i(a_f-a_i)^3}{s_i^2}+\frac{2j_i}{3s_i^3}(j_i^3-3a_is_ij_i+3v_is_i^2)s-(\frac{2}{3a_is_i}j_i^2-1+\frac{j_i(j_i^3-3a_is_ij_i+3v_is_i^2)}{9a_i^2s_i^2}-\frac{1}{9a_i^2s_i^2}j_i^4)\frac{a_i^2(a_f-a_i)^2}{s_i^2}=(\frac{2}{3s_i^3}v_ij_i^4-\frac{2}{s_i^2}v_ia_ij_i^2+\frac{2}{s_i}v_i^2j_i)t+(v_i^2-\frac{1}{s_i}v_ia_ij_i+\frac{1}{3s_i^2}v_ij_i^3)t^2 </math>. Finally, observe that since <math>a_f-a_i=j_it+\frac{1}{2}s_it^2</math>, <math>(\frac{2}{3s_i^3}v_ij_i^4-\frac{2}{s_i^2}v_ia_ij_i^2+\frac{2}{s_i}v_i^2j_i)t+(v_i^2-\frac{1}{s_i}v_ia_ij_i+\frac{1}{3s_i^2}v_ij_i^3)t^2=(\frac{2}{3s_i^3}v_ij_i^3-\frac{2}{s_i^2}v_ia_ij_i+\frac{2}{s_i}v_i^2)(a_f-a_i)</math>, <math>s^2-\frac{s(a_f-a_i)^2}{3s_i}+\frac{(a_f-a_i)^4}{36s_i^2}+(\frac{2}{3a_is_i}j_i^2-2)\frac{a_is(a_f-a_i)}{s_i}+(\frac{1}{3}-\frac{1}{9a_is_i}j_i^2)\frac{a_i(a_f-a_i)^3}{s_i^2}+\frac{2j_i}{3s_i^3}(j_i^3-3a_is_ij_i+3v_is_i^2)s-(\frac{2}{3a_is_i}j_i^2-1+\frac{j_i(j_i^3-3a_is_ij_i+3v_is_i^2)}{9a_i^2s_i^2}-\frac{1}{9a_i^2s_i^2}j_i^4)\frac{a_i^2(a_f-a_i)^2}{s_i^2}=(\frac{2}{3s_i^3}v_ij_i^3-\frac{2}{s_i^2}v_ia_ij_i+\frac{2}{s_i}v_i^2)(a_f-a_i) </math>, and our original equation is true. == Constant crackle == === Displacement-independent equations === There are 67 displacement-independent equations under constant crackle, inherited from the equations for constant snap, 19 of which are velocity-independent, and five of which are also acceleration-independent. <math>s_f=s_i+ct</math>, <math>j_f-j_i=\frac{s_f+s_i}{2}t</math>, <math>j_f-j_i=s_it+\frac{1}{2}ct^2</math>, <math>j_f-j_i=s_ft-\frac{1}{2}ct^2</math>, and <math>s_f^2=s_i^2+2c(j_f-j_i)</math>. {| class="wikitable" |+Velocity-independent equations ! colspan="6" |Present? ! rowspan="2" |Formula |- !j_f !s_f !j_i !s_i !c !t |- |F |F |T |T |T |T |<math>a_f-a_i=j_it+\frac{1}{2}s_it^2+\frac{1}{6}ct^3</math> |- |F |T |F |T |T |T |n/a |- |F |T |T |F |T |T |<math>a_f-a_i=j_it+\frac{1}{2}s_ft^2-\frac{1}{3}ct^3</math> |- |F |T |T |T |F |T |<math>a_f-a_i=j_it+(\frac{1}{3}s_i+\frac{1}{6}s_f)t^2</math> |- |F |T |T |T |T |F |<math>6c^2(a_f-a_i)=6j_ic(s_f-s_i)+(s_f+2s_i)(s_f-s_i)^2</math> |- |T |F |F |T |T |T |<math>a_f-a_i=j_f t-\frac{1}{2}s_it^2-\frac{1}{3}ct^3</math> |- |T |F |T |F |T |T |<math>a_f-a_i=\frac{j_f+j_i}{2}t-\frac{1}{12}ct^3</math> |- |T |F |T |T |F |T |<math>a_f-a_i=(\frac{2}{3}j_i+\frac{1}{3}j_f)t+\frac{1}{6}s_it^2</math> |- |T |F |T |T |T |F |<math>9c^2(a_f-a_i)^2-6s_i(s_i^2-3cj_i)(a_f-a_i)=(j_f-j_i)(2c(j_f+2j_i)^2-3s_i^2(j_f+j_i))</math> |- |T |T |F |F |T |T |<math>a_f-a_i=j_ft-\frac{1}{2}s_ft^2+\frac{1}{6}ct^3</math> |- |T |T |F |T |F |T |<math>a_f-a_i=j_ft-(\frac{1}{6}s_i+\frac{1}{3}s_f)t^2</math> |- |T |T |F |T |T |F |<math>6c^2(a_f-a_i)=6j_fc(s_f-s_i)-(2s_f+s_i)(s_f-s_i)^2</math> |- |T |T |T |F |F |T |<math>a_f-a_i=(\frac{1}{3}j_i+\frac{2}{3}j_f)t-\frac{1}{6}s_ft^2</math> |- |T |T |T |F |T |F |<math>9j^2s^2+6a_f(a_f^2-3jv_f)s=(v_f-v_i)(3a_f^2(v_f+v_i)-2j(2v_f+v_i)^2)</math> |- |T |T |T |T |F |F |<math>\frac{3(s_f+s_i)^2(a_f-a_i)}{2(j_f-j_i)}=s_ij_i+2s_ij_f+2j_is_f+s_fj_f</math> |} === Displacement-dependent equations === Since <math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+\frac{1}{24}s_it^4+\frac{1}{120}ct^5</math> (derived from the Taylor series expansion), displacement-dependent equations assuming constant snap must include six parameters (in this case, v_i, a_i, j_i, s_i, c, and t), giving 210 different possible equations. Here's a table of equations: {| class="wikitable" |+ ! colspan="10" |Present? ! rowspan="2" |Formula ! rowspan="2" |Explanation |- !v_f !a_f !j_f !s_f !v_i !a_i !j_i !s_i !c !t |- |F |F |F |F |T |T |T |T |T |T |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+\frac{1}{24}s_it^4+\frac{1}{120}ct^5</math> |Taylor series expansion |- |F |F |F |T |F |T |T |T |T |T |n/a |Parameters aren't independent, since <math>s_f=s_i+ct</math> |- |F |F |F |T |T |F |T |T |T |T |n/a |Parameters aren't independent, since <math>s_f=s_i+ct</math> |- |F |F |F |T |T |T |F |T |T |T |n/a |Parameters aren't independent, since <math>s_f=s_i+ct</math> |- |F |F |F |T |T |T |T |F |T |T |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+\frac{1}{24}s_ft^4-\frac{1}{30}ct^5</math> |Substituting s_i with <math>s_f-ct</math> |- |F |F |F |T |T |T |T |T |F |T |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+(\frac{1}{120}s_f+\frac{1}{30}s_i)t^4</math> |Substituting c with <math>\frac{s_f-s_i}t</math> |- |F |F |F |T |T |T |T |T |T |F | | |- |F |F |T |F |F |T |T |T |T |T |n/a |Parameters aren't independent, since <math>j_f-j_i=s_it+\frac{1}{2}ct^2</math> |- |F |F |T |F |T |F |T |T |T |T |n/a |Parameters aren't independent, since <math>j_f-j_i=s_it+\frac{1}{2}ct^2</math> |- |F |F |T |F |T |T |F |T |T |T |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_ft^3-\frac{1}{8}s_it^4-\frac{3}{40}ct^5</math> |Substituting j_i with <math>j_f-s_it-\frac{1}{2}ct^2</math> |- |F |F |T |F |T |T |T |F |T |T |<math>s=v_it+\frac{1}{2}a_it^2+(\frac{1}{24}j_f+\frac{1}{8}j_i)t^3-\frac{1}{80}ct^5</math> |Substituting s_i with <math>\frac{j_f-j_i}{t}-\frac{1}{2}ct</math> |- |F |F |T |F |T |T |T |T |F |T |<math>s=v_it+\frac{1}{2}a_it^2+(\frac{1}{60}j_f+\frac{3}{20}j_i)t^3+\frac{1}{40}s_it^4</math> |Substituting c with <math>\frac{2(j_f-j_i-s_it)}{t^2}</math> |- |F |F |T |F |T |T |T |T |T |F | | |- |F |F |T |T |F |F |T |T |T |T |n/a |Parameters aren't independent, since <math>s_f=s_i+ct</math> |- |F |F |T |T |F |T |F |T |T |T |n/a |Parameters aren't independent, since <math>s_f=s_i+ct</math> |- |F |F |T |T |F |T |T |F |T |T |n/a |Parameters aren't independent, since <math>j_f-j_i=s_ft-\frac{1}{2}ct^2</math> |- |F |F |T |T |F |T |T |T |F |T |n/a |Parameters aren't independent, since <math>j_f-j_i=\frac{s_f+s_i}{2}t</math> |- |F |F |T |T |F |T |T |T |T |F |n/a |Parameters aren't independent, since <math>s_f^2=s_i^2+2c(j_f-j_i)</math> |- |F |F |T |T |T |F |F |T |T |T |n/a |Parameters aren't independent, since <math>s_f=s_i+ct</math> |- |F |F |T |T |T |F |T |F |T |T |n/a |Parameters aren't independent, since <math>j_f-j_i=s_ft-\frac{1}{2}ct^2</math> |- |F |F |T |T |T |F |T |T |F |T |n/a |Parameters aren't independent, since <math>j_f-j_i=\frac{s_f+s_i}{2}t</math> |- |F |F |T |T |T |F |T |T |T |F |n/a |Parameters aren't independent, since <math>s_f^2=s_i^2+2c(j_f-j_i)</math> |- |F |F |T |T |T |T |F |F |T |T |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_ft^3-\frac{1}{8}s_ft^4+\frac{1}{20}ct^5</math> |Substituting j_i with <math>j_f-s_ft+\frac{1}{2}ct^2</math> and s_i with <math>s_f-ct</math> |- |F |F |T |T |T |T |F |T |F |T |<math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_ft^3-(\frac{3}{40}s_f+\frac{1}{20}s_i)t^4</math> |Substituting j_i with <math>j_f-\frac{s_f+s_i}{2}t</math> and c with <math>\frac{s_f-s_i}t</math> |- |F |F |T |T |T |T |F |T |T |F | | |- |F |F |T |T |T |T |T |F |F |T | | |- |F |F |T |T |T |T |T |F |T |F | | |- |F |F |T |T |T |T |T |T |F |F | | |- |F |T |F |F |F |T |T |T |T |T |n/a |Parameters aren't independent, since <math>a_f-a_i=j_it+\frac{1}{2}s_it^2+\frac{1}{6}ct^3</math> |- |F |T |F |F |T |F |T |T |T |T |<math>s=v_it+\frac{1}{2}a_ft^2-\frac{1}{3}j_it^3-\frac{5}{24}s_it^4-\frac{3}{40}ct^5</math> |Substituting a_i with <math>a_f-j_it-\frac{1}{2}s_it^2-\frac{1}{6}ct^3</math> |- |F |T |F |F |T |T |F |T |T |T |<math>s=v_it+(\frac{1}{6}a_f+\frac{1}{3}a_i)t^2+-\frac{1}{24}s_it^4-\frac{7}{360}ct^5</math> |Substituting j_i with <math>\frac{a_f-a_i}{t}-\frac{1}{2}s_it-\frac{1}{6}ct^2</math> |- |F |T |F |F |T |T |T |F |T |T |<math>s=v_it+(\frac{1}{12}a_f+\frac{5}{12}a_i)t^2+\frac{1}{12}j_it^3-\frac{1}{180}ct^5</math> |Substituting s_i with <math>\frac{2(a_f-a_i-j_it)}{t^2}-\frac{1}{3}ct</math> |- |F |T |F |F |T |T |T |T |F |T |<math>s=v_it+(\frac{1}{20}a_f+\frac{9}{20}a_i)t^2+\frac{7}{60}j_it^3+\frac{1}{60}s_it^4</math> |Substituting c with <math>\frac{6(a_f-a_i-j_it)-3s_it^2}{t^3}</math> |- |F |T |F |F |T |T |T |T |T |F | | |- |F |T |F |T |F |F |T |T |T |T |n/a |Parameters aren't independent, since <math>s_f=s_i+ct</math> |- |F |T |F |T |F |T |F |T |T |T |n/a |Parameters aren't independent, since <math>s_f=s_i+ct</math> |- |F |T |F |T |F |T |T |F |T |T |n/a |Parameters aren't independent, since <math>a_f-a_i=j_it+\frac{1}{2}s_ft^2-\frac{1}{3}ct^3</math> |- |F |T |F |T |F |T |T |T |F |T |n/a |Parameters aren't independent, since <math>a_f-a_i=j_it+(\frac{1}{3}s_i+\frac{1}{6}s_f)t^2</math> |- |F |T |F |T |F |T |T |T |T |F |n/a |Parameters aren't independent, since <math>6c^2(a_f-a_i)=6j_ic(s_f-s_i)+(s_f+2s_i)(s_f-s_i)^2</math> |- |F |T |F |T |T |F |F |T |T |T |n/a |Parameters aren't independent, since <math>s_f=s_i+ct</math> |- |F |T |F |T |T |F |T |F |T |T |<math>s=v_it+\frac{1}{2}a_ft^2-\frac{1}{3}j_it^3-\frac{5}{24}s_ft^4+\frac{2}{15}ct^5</math> |Substituting a_i with <math>a_f-j_it-\frac{1}{2}s_ft^2+\frac{1}{3}ct^3</math> and s_i with <math>s_f-ct</math> |- |F |T |F |T |T |F |T |T |F |T |<math>s=v_it+\frac{1}{2}a_ft^2-\frac{1}{3}j_it^3-(\frac{3}{40}s_f+\frac{2}{15}s_i)t^4</math> |Substituting a_i with <math>a_f-j_it-(\frac{1}{3}s_i+\frac{1}{6}s_f)t^2</math> and c with <math>\frac{s_f-s_i}t</math> |- |F |T |F |T |T |F |T |T |T |F | | |- |F |T |F |T |T |T |F |F |T |T |<math>s=v_it+(\frac{1}{6}a_f+\frac{1}{3}a_i)t^2-\frac{1}{24}s_ft^4+\frac{1}{45}ct^5</math> |Substituting j_i with <math>\frac{a_f-a_i}{t}-\frac{1}{2}s_ft+\frac{1}{3}ct^2</math> and s_i with <math>s_f-ct</math> |- |F |T |F |T |T |T |F |T |F |T | | |- |F |T |F |T |T |T |F |T |T |F | | |- |F |T |F |T |T |T |T |F |F |T | | |- |F |T |F |T |T |T |T |F |T |F | | |- |F |T |F |T |T |T |T |T |F |F | | |- |F |T |T |F |F |F |T |T |T |T |n/a |Parameters aren't independent, since <math>j_f-j_i=s_it+\frac{1}{2}ct^2</math> |- |F |T |T |F |F |T |F |T |T |T |n/a |Parameters aren't independent, since <math>a_f-a_i=j_f t-\frac{1}{2}s_it^2-\frac{1}{3}ct^3</math> |- |F |T |T |F |F |T |T |F |T |T |n/a |Parameters aren't independent, since <math>a_f-a_i=\frac{j_f+j_i}{2}t-\frac{1}{12}ct^3</math> |- |F |T |T |F |F |T |T |T |F |T |n/a |Parameters aren't independent, since <math>a_f-a_i=(\frac{2}{3}j_i+\frac{1}{3}j_f)t+\frac{1}{6}s_it^2</math> |- |F |T |T |F |F |T |T |T |T |F |n/a |Parameters aren't independent, since <math>9c^2(a_f-a_i)^2-6s_i(s_i^2-3cj_i)(a_f-a_i)=(j_f-j_i)(2c(j_f+2j_i)^2-3s_i^2(j_f+j_i))</math> |- |F |T |T |F |T |F |F |T |T |T | | |- |F |T |T |F |T |F |T |F |T |T | | |- |F |T |T |F |T |F |T |T |F |T | | |- |F |T |T |F |T |F |T |T |T |F | | |- |F |T |T |F |T |T |F |F |T |T | | |- |F |T |T |F |T |T |F |T |F |T | | |- |F |T |T |F |T |T |F |T |T |F | | |- |F |T |T |F |T |T |T |F |F |T | | |- |F |T |T |F |T |T |T |F |T |F | | |- |F |T |T |F |T |T |T |T |F |F | | |- |F |T |T |T |F |F |F |T |T |T |n/a |Parameters aren't independent, since |- |F |T |T |T |F |F |T |F |T |T |n/a |Parameters aren't independent, since |- |F |T |T |T |F |F |T |T |F |T |n/a |Parameters aren't independent, since |- |F |T |T |T |F |F |T |T |T |F |n/a |Parameters aren't independent, since |- |F |T |T |T |F |T |F |F |T |T | | |- |F |T |T |T |F |T |F |T |F |T | | |- |F |T |T |T |F |T |F |T |T |F | | |- |F |T |T |T |F |T |T |F |F |T | | |- |F |T |T |T |F |T |T |F |T |F | | |- |F |T |T |T |F |T |T |T |F |F | | |- |F |T |T |T |T |F |F |F |T |T | | |- |F |T |T |T |T |F |F |T |F |T | | |- |F |T |T |T |T |F |F |T |T |F | | |- |F |T |T |T |T |F |T |F |F |T | | |- |F |T |T |T |T |F |T |F |T |F | | |- |F |T |T |T |T |F |T |T |F |F | | |- |F |T |T |T |T |T |F |F |F |T | | |- |F |T |T |T |T |T |F |F |T |F | | |- |F |T |T |T |T |T |F |T |F |F | | |- |F |T |T |T |T |T |T |F |F |F | | |} == Constant pop == === Displacement-independent equations === There are displacement-independent equations under constant pop, inherited from the equations for constant crackle, 67 of which are velocity-independent, 19 of which are also acceleration-independent, and five of which are also jerk-independent === Displacement-dependent equations === Since <math>s=v_it+\frac{1}{2}a_it^2+\frac{1}{6}j_it^3+\frac{1}{24}s_it^4+\frac{1}{120}c_it^5+\frac{1}{720}pt^6</math> (derived from the Taylor series expansion), displacement-dependent equations assuming constant snap must include six parameters (in this case, v_i, a_i, j_i, s_i, c_i, p, and t), giving 792 different possible equations. Here's a table of equations: [[Category:Physics]] duzc1t03gek4tgh8b89cpu7hnoj226c 0 305987 2835460 2833008 2026-10-02T04:48:30Z U3253354 3109187 Corrected spelling and wording for clarity 2835460 wikitext text/x-wiki {{title|Basal ganglia and motivation:<br>What is the role of the basal ganglia in motivated behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=5}} ; Scenario * Imagine you are a university student. * You have to choose between delayed gratification (study) or instant gratification (new book from favourite author) * Basal ganglia processes reward info for bahaviour selection * Dopaminergic influence * Behaviour {{RoundBoxBottom}} '''Explanation of the problem, issue, or topic''': Brief explanation of the problem, why it is important, and an outline of how psychological science can help {{RoundBoxTop|theme=3}} '''Focus questions''' Break the sub-title down into three to five [[Motivation and emotion/Assessment/Chapter/Focus questions|focus questions]]. Align the top-level headings with these focus questions. * What is the relationship between motivation and the basal ganglia? * What is the relationship between the basal ganglia and dopamine? * What are some potential issues if these relationships break down? {{RoundBoxBottom}} ==Headings== Planned additional headings: * Motivation and motivated behaviour * The basal ganglia and motivated behaviour *Dopamine and motivation *Links to disorders ==Key points== * Motivation and motived behaviour ** What is motivation ** What is motivated behaviour ** Motivational influence on behaviour and selection *Basal Ganglia **Anatomy ***Physical organisation ***Key regions **Function ***Managing signals (behaviour and selection) ***Responsible for movement - direct route, indirect route, hyperdirect route **Role in motivation and motivated behaviour (motivation + behaviour) *Dopamine **Pathways[[File:Dopaminergic pathways.svg|none|thumb|'''Figure 1.''' The main dopaminergic pathways of the brain.|450x450px]] **Reward circuit **Substantia niagra (Ikemoto et al., 2015) **Biases go circuit (damage linked to Parkinson's) **Link to Basal Ganglia and motivation/motivated behaviour *Links to disorders **Parkinson's disease ***Linked to basal ganglia and dopamine ***Cognitive deficits in executive function **ADHD (Shaw et al., 2014) <quiz display="simple"> Parkinson's disease is linked to damage in the Mesocortical pathway |type="()"} - True + False {Parkinson's disease is linked to damage in the Mesolimbic pathway |type="()"} - True + False {Parkinson's disease is linked to damage in the Tuberoinfundibular pathway |type="()"} - True + False {Parkinson's disease is linked to damage in the Nigrostriatal pathway |type="()"} + True - False </quiz> ==Conclusion== * Arguably the most important section * Provide at least three bullet-points for this section even at the topic development stage, based on preliminary thinking * For the book chapter, develop clear take-home message(s) that address the focus questions based on psychological theory and research * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing this problem * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== * [[Motivation and emotion/Book/2023/Basal ganglia and motivation|Basal ganglia and motivation]] (Book chapter, 2023) * [[wikipedia:Dopaminergic_pathways|Dopaminergic pathways]] (Wikipedia) {{tip|Suggestions for this section: * Link to the most relevant internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Berridge, K. C. (2007). The debate over dopamine’s role in reward: The case for incentive salience. Psychopharmacology, 191(3), 391–431. https://doi.org/10.1007/s00213-006-0578-x Berridge, K. C., & Robinson, T. E. (2016). Liking, wanting, and the incentive-sensitization theory of addiction. American Psychologist, 71(8), 670–679. https://doi.org/10.1037/amp0000059 Bromberg-Martin, E. S., Matsumoto, M., & Hikosaka, O. (2010). Dopamine in motivational control: Rewarding, aversive, and alerting. Neuron, 68(5), 815–834. https://doi.org/10.1016/j.neuron.2010.11.022 Da Cunha C, Gomez-A A, Blaha CD. The role of the basal ganglia in motivated behavior. Rev Neurosci. 2012;23(5-6):747-67. doi: 10.1515/revneuro-2012-0063. PMID: 23079510. Dudman, J. T., & Krakauer, J. W. (2016). The basal ganglia: from motor commands to the control of vigor. Current opinion in neurobiology, 37, 158-166. Hikosaka, O., Bromberg-Martin, E., Hong, S., & Matsumoto, M. (2014). Multi-level control of reward-guided behavior by the basal ganglia. Nature Reviews Neuroscience, 15(8), 641–654. https://doi.org/10.1038/nrn3789 Ikemoto S, Yang C, Tan A. Basal ganglia circuit loops, dopamine and motivation: A review and enquiry. Behav Brain Res. 2015 Sep 1;290:17-31. doi: 10.1016/j.bbr.2015.04.018. Epub 2015 Apr 20. PMID: 25907747; PMCID: PMC4447603. Kim, H. F., & Hikosaka, O. (2015). Parallel basal ganglia circuits for voluntary and automatic behaviour to reach rewards. Brain, 138(7), 1776-1800. Salamone, J. D., Yohn, S. E., López-Cruz, L., San Miguel, N., & Correa, M. (2018). Activational and effort-related aspects of motivation: Neural mechanisms and implications for psychopathology. Brain, 141(2), 331–345. https://doi.org/10.1093/brain/awx268 Schultz, W. Reward functions of the basal ganglia. J Neural Transm 123, 679–693 (2016). https://doi.org/10.1007/s00702-016-1510-0 Shaw P, De Rossi P, Watson B, Wharton A, Greenstein D, Raznahan A, Sharp W, Lerch JP, Chakravarty MM. Mapping the development of the basal ganglia in children with attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry. 2014 Jul;53(7):780-9.e11. doi: 10.1016/j.jaac.2014.05.003. Epub 2014 May 20. PMID: 24954827; PMCID: PMC10461726. Yin, H. H., & Knowlton, B. J. (2006). The role of the basal ganglia in habit formation. Nature Reviews Neuroscience, 7(6), 464–476. https://doi.org/10.1038/nrn1919 }} ==External links== [[Help:Contents/Links#External_links|External links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Link to the most relevant external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] og59uco8scmdfr6ptarr3h16ng7hiby 0 307863 2835496 2789320 2026-10-02T11:08:45Z Dick Bos 24466 cat 2835496 wikitext text/x-wiki This resource gives information on [[Karl Marx]]'s '''[[:w:en:Critique of political economy|critique of political economy]].''' == ''Capital'' == The most well-known work of Marx on political economy is of course ''Das Kapital : Kritik der politischen Oekonomie'' (Capital : A Critique of Political Economy). * The first volume (Der Produktionsprocess des Kapitals - The Process of Production of Capital) was first published 1867.<ref name=C1>We will use the title ''Capital 1'' in this resources.</ref> * The second volume, on 'The Process of Circulation of Capital' was not completed by Marx, and was published posthumously by Friedrich Engels, in 1885. * The third volume, on 'The Process of Capitalist Production as a Whole,' was also published by Engels, in 1894. * ''Theorien über den Mehrwert'' (Theories of Surplus Value) is sometimes considered volume 4 of ''Das Kapital''. == Some other writings on political economy == Marx did also write other works on political economy, some of which were not all intended for publication, e.g.: * ''Economic and Philosophic Manuscripts of 1844,'' commonly known as the Paris manuscripts, written in 1844, first published 1932. * ''Lohnarbeit und Kapital'' (''[[:s:en:Wage-Labour and Capital|Wage-Labour and Capital]]''), a lecture of 1847, first published 1849. * ''Grundrisse der Kritik der Politische Ökonomie'' (''Foundations of a Critique of Political Economy''), a very extensive manuscript, written 1857-1858 as a draft for ''Capital,'' that was left aside, and was first published in 1939. * ''Zur Kritik der Politischen Oekonomie'' (''A Contribution to the Critique of Political Economy''), first published 1859. * ''Lohn, Preis und Profit'' (''Value, Price and Profit''), an English-language lecture of 1865, first published 1898. Apart from this it is important to mention publications by Friedrich Engels, like * 'Umrisse zu einer Kritik der Nationalökonomie' ('Outlines of a Critique of Political Economy', 1844). == Development == On the development of Marx's economic theory a lot has been written. * An introductory text was published by Witali Wygodski, originally in Russian, in 1965. ** German: ''Die Geschichte einer grossen Entdeckung'' (1967)<ref name=WygodskiDe>Berlin : Verlag Die Wirtschaft.</ref> ** ''The Story of a Great Discovery : How Karl Marx wrote "Capital"'' (1974)<ref name=WygodskiEn>Tunbridge Wells : Abacus Press. {{ISBN|0 85626 075 4}}. [https://archive.org/details/storyofgreatdisc0000vygo Available to borrow] in Internet Archive.</ref> ** Dutch: ''De ontwikkeling van het ekonomies denken van Marx : de geschiedenis van een grote ontdekking'' (1974)<ref name=WygodskiNl>Nijmegen : SUN. {{ISBN|90 6168 062 X}}</ref> * A more "modern" introduction was written by Francis Wheen in 2006: ''Marx's Das Kapital : a biography''<ref name=Wheen2006>London : Atlantic Books. {{ISBN|978 1 84354 401 2}}. ([https://books.google.nl/books?id=QuVGDgAAQBAJ Partial in Google Books].)</ref> * A very fundamental analysis is given in Rosdolsky, originally in German, 1968. ** German: ''Zur Entstehungsgeschichte des Marx'schen Kapital : Der Rohentwurf des Kapital 1857–1858'' (1968; The genesis of Marx's Capital : the draft of Capital 1857–1858) in 2 volumes (one of the first texts that delivered a comprehensive treatment of the ''Grundrisse'')<ref name=RosdolskyDe>Frankfurt am Main : Europäische Verlagsanstalt. {{ISBN|3 434 45003 3}}. [https://archive.org/details/zurentstehungsge0000rozd Vol. 1] and [https://archive.org/details/zurentstehungsge0000rozd_e6n6 Vol. 2] available to borrow in Internet Archive.</ref> ** ''The making of Marx's Capital'' (1977)<ref name=RosdolskyEn>London : Pluto Press. {{ISBN|9780904383379}}. [https://archive.org/details/makingofmarxscap0000rozd Available to borrow] in Internet Archive.</ref> == ''Capital 1'' == The first volume of ''Capital'' bears the title 'The Process of Production of Capital,' and deals with fundamental concepts, related to the study of capitalist economy. Some of these concepts are: value, use value, exchange value, surplus value, wage labour, and of course capital. The systematic development of these concepts takes more than a thousand pages.<ref name=thousand>In the Pelican edition 1976.</ref> No easy stuff. Especially the first chapters are a big hindrance for studying Marx's ideas. But there are works to help you through this rice pudding, like for instance [[:w:en:David Harvey|David Harvey's]] lectures and companions (2007-2022).<ref name=Harvey>[https://davidharvey.org/reading-capital/ Harvey's lectures online on Marx's Capital (and Grundrisse)] and ''[https://archive.org/details/companiontomarxs0000harv Companion to vol. 1]''</ref><ref name=Harveycrit>For a critical view on Harvey's ''Companion'', chapter 1, see: {{cite web | url = https://critisticuffs.org/texts/david-harvey/ | title = Critisticuffs—A Companion to David Harvey's Companion to Marx' Capital, Chapter 1 | website = critisticuffs.org | access-date = 2025-05-23 | archive-url = https://web.archive.org/web/20250207204827/https://critisticuffs.org/texts/david-harvey/ | archive-date = 2025-02-07 }}</ref> Another comprehensive study guide is given by [[:w:en:Harry Cleaver|Harry Cleaver]] (published 1979-2019).<ref name=Cleaver>"[https://la.utexas.edu/users/hcleaver/357k/357ksg.html Study Guide to Capital I]" and "[https://la.utexas.edu/users/hcleaver/357k/357krcp.html Reading Capital politically]" by Harry Cleaver.</ref> A comparatively short "Reading Guide" is written by [[:w:en:Simon Clarke (sociologist)|Simon Clarke]].<ref name=Clarke>"[https://archive.org/details/ReadingGuideToCapitalVolume1SimonClarke Reading Guide to Capital I]" by Simon Clarke.</ref> [[Karl Marx/Capital1|''Capital 1'']] holds eight parts (and an appendix): * [[Karl Marx/Capital1/Part1|Part 1]]: Commodities and Money * [[Karl Marx/Capital1/Part2|Part 2]]: The Transformation of Money into Capital * [[Karl Marx/Capital1/Part3|Part 3]]: The Production of Absolute Surplus-Value * [[Karl Marx/Capital1/Part4|Part 4]]: The Production of Relative Surplus-Value * [[Karl Marx/Capital1/Part5|Part 5]]: The Production of Absolute and Relative Surplus-Value * [[Karl Marx/Capital1/Part6|Part 6]]: Wages * [[Karl Marx/Capital1/Part7|Part 7]]: The Process of Accumulation of Capital * [[Karl Marx/Capital1/Part8|Part 8]]: So-Called Primitive Accumulation * [[Karl Marx/Capital1/App|Appendix]]: Results of the Immediate Process of Production == External links to the (English) texts == * [https://www.marxists.org/archive/marx/works/1867-c1/index.htm ''Capital,'' 1st volume] in English translation at marxists.org * [https://www.marxists.org/archive/marx/works/1885-c2/index.htm ''Capital,'' 2nd volume] (English transl.) * [https://www.marxists.org/archive/marx/works/1894-c3/index.htm ''Capital,'' 3rd volume] (English transl.) * [https://www.marxists.org/archive/marx/works/1863/theories-surplus-value/ ''Theories of Surplus-Value''] at marxists.org * [https://www.marxists.org/archive/marx/works/1844/manuscripts/preface.htm Paris manuscripts] * [https://www.marxists.org/archive/marx/works/1847/wage-labour/index.htm ''Wage Labour and Capital''] * [https://www.marxists.org/archive/marx/works/1857/grundrisse/index.htm ''Grundrisse''] * [https://www.marxists.org/archive/marx/works/1859/critique-pol-economy/index.htm ''A Contribution to the Critique of Political Economy''] * [https://www.marxists.org/archive/marx/works/1865/value-price-profit/ ''Value, Price and Profit''] * [https://www.marxists.org/archive/marx/works/1844/df-jahrbucher/outlines.htm ''Outlines of a Critique of Political Economy''] by Friedrich Engels == Footnotes == {{References}} {{DEFAULTSORT:Marx, Karl - Critique of Political Economy}} [[Category:History of Economic Thought]] {{BookCat}} psvl7yhv8ybvs8uekzlcflurpfi4m8d 0 318047 2835336 2787758 2026-10-01T12:28:58Z Lbeaumont 278565 /* The Role of Skepticism and Critical Thinking */ Added questios for a deeper analysis 2835336 wikitext text/x-wiki {{AI-generated}} —Fact or fiction? {{TOC right | limit|limit=2}} [[File:Truth meter.jpg|thumb|Is this fact or fiction?]] == Introduction == Because we are flooded with [[w:Information|information]], some accurate, some not, it is helpful to be able to accurately evaluate the truth-value of information. [[w:Brandolini's_law|Brandolini's]] law reminds us that “The amount of energy needed to refute [[w:Bullshit|bullshit]] is an order of magnitude bigger than that needed to produce it”. Learn to recognize, avoid, and dispose of nonsense. It is useful to be able to navigate the [[w:DIKW_pyramid|DIKW pyramid]]. This course focuses on evaluating information that is presented as factual and informative. Enjoy any works of [[w:Fiction|fiction]] you find entertaining or amusing. Indulge opinions on fashion and matters of taste. Enjoy and reflect on [[Intellectual honesty|intellectually honest]] arguments and debates on [[Facing Facts#Degrees of Consensus|matters of controversy]], while keeping in mind that the [[/The Best Story Often Wins/|best story often wins]]. Do not be fooled by false, misleading, or deceptive information that is represented as being objective and factual.   Whether you [[/Hunting or Hunted?/|hunted down the information]], or the information hunted for you, it is wise to determine if the information is factual, or if you are being misled. [[Facing Facts#The Importance of Truth|Facts are our friends]]! The Wikiversity course [[Information literacy and researching skills]] covers similar topics and may be a useful supplement to this course. == Objectives == The objective of this course is to help students identify misleading or deceptive information that is represented as being objective and factual. Use this [[/Daily Practice: Evaluating Information/|daily practice checklist]] to make evaluating information a habit. This course has no prerequisites, and all students are welcome. Several companion courses are available that can help students gain additional background or bolster their understanding of various concepts and techniques useful in evaluating information. These include: * [[Facing Facts]] — Embracing Reality * [[Evaluating Journalism Standards]] — Seeking reliable information sources * [[Intellectual honesty|Intellectual Honesty]] — Accurately communicating true beliefs * [[Virtues/Good Faith]] – The virtue of truthfullness * [[Forming beliefs|Forming Beliefs]] — Evaluating what you accept as true * [[Knowing How You Know|Knowing how you know]] * [[Seeking True Beliefs]] —Excellence in the Quest for Knowledge * [[Evaluating Evidence]] — Seeking Reality * [[Navigating Social Proof]] —Going along to get along Study these companion courses any time they may be helpful. Specific companion course suggestions appear in relevant sections throughout this course. == Motivations toward true beliefs == Unless you are motivated to choose true beliefs, nonsense is as valuable to you as factual information. The [[Seeking True Beliefs#The Intellectual Virtues|intellectual virtues]] are motivations toward true beliefs. Various researchers have identified a variety of intellectual virtues. To avoid nonsense, work to develop and practice the intellectual virtues. === Assignment === # Read the essay [[/Benefits of True Beliefs/|Benefits of True Beliefs]]. # Study the [[Seeking True Beliefs/Reasons to seek true beliefs|Reasons to seek true beliefs]] section of the Wikiversity course [[Seeking True Beliefs]]. # Study the [[Facing Facts#The Importance of Truth|Importance of Truth]] section of the Wikiversity course [[Facing Facts]]. # Study the [[Seeking True Beliefs#The Intellectual Virtues|Intellectual Virtues section]] of the Wikiversity course [[Seeking True Beliefs]]. # Work to develop and practice the intellectual virtues. == Fact or Fiction? == In a world flooded with information, distinguishing fact from fiction has become a critical skill.<ref>[[w:ChatGPT|ChatGPT]] generated this text responding to the prompt: “Write an extended essay with the title “Fact or Fiction” Describe information characteristics that distinguish accurate, factual, representative, and objective information from false, misleading, or deceptive misinformation and disinformation. Discuss propaganda tactics, how they can be identified, and avoided. Address building digital Literacy: authenticating authorship, spotting fakes, verifying images, videos, and data online”.</ref> Accurate, factual, representative, and objective information is essential for making informed decisions, fostering trust, and maintaining healthy societies. Yet, false, misleading, and deceptive content—[[w:Misinformation|misinformation]] and [[w:Disinformation|disinformation]]—has proliferated, eroding the boundaries between reality and fabrication. Navigating this complex landscape requires understanding the characteristics of reliable information, recognizing [[w:Propaganda_techniques|propaganda tactics]], and building [[w:Digital_literacy|digital literacy]] skills to [[w:Authentication|authenticate]] and verify the content we consume. This section of the course explores these themes, providing tools to differentiate fact from fiction and safeguard our understanding of truth. === Characteristics of Accurate, Factual, Representative, and Objective Information === Reliable information possesses several defining characteristics that distinguish it from false or misleading content. Recognizing these traits is the first step in evaluating the credibility of any source. '''1. Accuracy''' * Accurate information is factually correct and verifiable through [[w:Independent_sources|independent sources]]. * It is free of errors, [[w:Contradiction|contradictions]], or distortions. * Accurate content provides supporting [[Evaluating Evidence|evidence]], such as data, [[w:Citation|citations]], or firsthand accounts, to back its claims. '''2. Factuality''' * [[Facing Facts|Factual information]] is grounded in [[Facing Facts/Reality is our common ground|objective reality]], based on representative [[Evaluating Evidence|evidence]] rather than opinions, emotions, or speculation. * [[w:Fact|Facts]] are observable, measurable, and often repeatable in nature (e.g., [[Thinking Scientifically|scientific findings]] or documented historical events). '''3. Representativeness''' * Representative information fairly reflects the subject or situation it describes, avoiding [[w:Cherry_picking|cherry-picking]] data or presenting selective narratives. * It accounts for the broader context, ensuring that conclusions are not drawn from isolated or atypical examples. '''4. Objectivity''' * Objective information avoids [[w:Bias|bias]], [[Intellectual honesty|honestly]] presenting all honest sides of an issue without favoring a particular perspective. * It uses neutral language, refrains from [[w:Manipulation_(psychology)|emotional manipulation]], and prioritizes clarity over persuasion. Together, these qualities form the foundation of credible and trustworthy information. Sources that exhibit these characteristics empower audiences to think critically and form informed opinions. === Characteristics of Misinformation and Disinformation === In contrast, [[w:Misinformation|misinformation]] and disinformation lack the qualities of credible information, often aiming to deceive, manipulate, or mislead. '''1. Misinformation''' * '''Definition''': False or inaccurate information shared without harmful intent. * Examples include [[w:Rumor|rumors]], misunderstood data, or outdated information. '''2. Disinformation''' * '''Definition''': Deliberately false information created to deceive or manipulate audiences. * [[w:Disinformation|Disinformation]] is often used to influence political opinions, promote agendas, or undermine trust in institutions. '''Red Flags of False Information:''' # '''Emotional Language''': Exaggerated or sensational tones designed to provoke anger, fear, or [[w:Outrage_(emotion)|outrage]]. # '''Lack of Evidence''': Claims unsupported by data, sources, or citations. # '''One-Sided Arguments''': Presenting only one perspective while ignoring counterarguments or alternative interpretations. # '''Manipulated Media''': Altered images, videos, or charts that misrepresent reality. # '''Anonymity or Hidden Authorship''': Sources with unclear, false, or misleading attribution or credentials. Understanding these traits is essential for recognizing and avoiding unreliable information. === Propaganda Tactics: Identification and Avoidance === [[w:Propaganda|Propaganda]] uses [[w:Manipulation_(psychology)|psychological]] and [[w:Rhetoric|rhetorical]] tactics to shape public perception and behavior, often blurring the lines between fact and fiction. These tactics exploit [[w:Cognitive_bias|cognitive biases]], emotions, and [[w:Social_dynamics|social dynamics]] to achieve their goals. '''1. Common Propaganda Tactics''' * '''[[w:Bandwagon_effect|Bandwagon Effect]]''': Encouraging people to adopt an idea because "everyone else is doing it." The Wikiversity course [[Navigating Social Proof]] elaborates on this. * '''Fear Appeals''': Exploiting fear to push an agenda or justify extreme actions. * '''[[w:Name_calling|Name-Calling]]''': Attacking opponents with derogatory labels to discredit them. * '''[[w:False_dilemma|False Dilemmas]]''': Presenting a complex issue as a binary choice, ignoring nuance or alternatives. The Wikiversity course [[Recognizing Fallacies]] elaborates on this and other fallacies. * '''Repetition''': Repeating false claims until they appear credible through familiarity (the "[[w:Illusory_truth_effect|illusory truth effect]]"). * '''Glittering Generalities''': Using vague but emotionally appealing phrases that lack specific meaning. '''2. Identifying Propaganda''' * '''Evaluate Language''': Look for emotionally charged words or exaggerated claims. * '''Analyze Intent''': Ask, “What is the purpose of this message? What are they trying to achieve?” * '''Check Sources''': Verify the credibility of the organization or individual promoting the message. '''3. Avoiding Propaganda''' * '''Question Assumptions''': Challenge oversimplified narratives and consider alternative viewpoints. * '''Seek Diverse Perspectives''': Avoid echo chambers by consulting a range of sources. * '''[[Facing Facts|Focus on Facts]]''': Prioritize evidence-based arguments over emotional appeals. By recognizing and resisting propaganda tactics, individuals can protect themselves from manipulation and make more informed decisions. === Building Digital Literacy === In the digital age, misinformation and disinformation spread rapidly through social media, websites, and other online platforms. Building [[w:Digital_literacy|digital literacy]]—the ability to critically evaluate online content—is essential for distinguishing fact from fiction. '''1. Authenticating Authorship''' * Check for clear attribution: Who wrote the content? Are they a credible expert? Are they [[Intellectual honesty|Intellectually honest]]? * Look for contact information, credentials, or affiliations that establish the author’s authority. * Be wary of anonymous content, as it often lacks accountability. '''2. Spotting Fakes''' * '''Identifying [[w:Fake_news|Fake News]]''': ** Examine the website: Does it have a professional layout, or is it riddled with ads and spelling errors? ** Investigate headlines: Does the headline sensationalize or exaggerate the content? ** Cross-check claims: Compare the content with reputable sources to verify accuracy. * '''Spotting Fake Accounts''': ** Check profile details: Fake accounts often have limited activity, generic profile pictures, or recently created profiles. '''3. Verifying Images and Videos''' * '''Reverse Image Search''': ** Use tools like [[w:Google_Images|Google Images]] or [[w:TinEye|TinEye]] to check whether an image has been altered or used out of context. * '''Metadata Analysis''': ** Examine [[w:Metadata|metadata]] (e.g., file creation dates) to confirm when and where a photo or video was taken. * '''Analyze Visual Cues''': ** Look for inconsistencies in lighting, shadows, or proportions that may indicate manipulation. '''4. Verifying Data and Statistics''' * '''Trace Data to Its Source''': ** Navigate [[Information literacy and researching skills#Types of information sources: primary, secondary, and tertiary|primary, secondary, and tertiary sources]] skillfully. ** Look for original research, reports, or studies. Avoid relying on secondary summaries that may misinterpret findings. * '''Evaluate Methodology''': ** Consider how the data was collected and whether it is representative of the population or topic it addresses. * '''Beware of Cherry-Picked Data''': ** Check for omitted context or selective presentation of statistics. === The Role of Skepticism and Critical Thinking === [[w:Skepticism|Skepticism]] and [[Clear Thinking/Curriculum|critical thinking]] are essential tools for navigating the modern information landscape. They allow individuals to question, evaluate, and validate the information they encounter. '''1. Adopt a Questioning Mindset''' * '''Ask Key Questions''': ** Who created this content, and why? ** What [[Evaluating Evidence|evidence]] supports these claims? ** Are there alternative explanations or perspectives? ** For a deeper analysis, consider these additional questions: *# ''What specific claim is being made?'' *# ''What concrete evidence supports it?'' *# ''What unstated assumptions are embedded?'' *# ''What perspective or context is missing?'' *# ''What alternative explanations exist?'' *# ''Who benefits from this framing?'' *# ''What evidence would falsify this claim?'' *# ''What does the model/source fail to know?'' *# ''What responsible action should follow?'' '''2. Cross-Check and Verify''' * Avoid relying on a single source. Consult multiple, [[w:Independent_sources|independent sources]] to corroborate information. * Doubt Rumors. [[w:Rumor|Rumors]] are unverified information circulating among people, especially without solid evidence. They are unreliable sources of information. Be diligent in verifying rumors before passing them on, or allowing them to influence your beliefs. Verify information before passing it on, including [[w:Like_button|likes]] reposting, and forwarding on social media. * Favor [[w:Primary_source|Primary Sources]]. Seek sources that are as close as possible to the event being reported. Avoid hearsay. Consult the original research papers to verify claims made in news releases or subsequent reporting. * Several organizations work to [[Evaluating Journalism Standards#Fact Checking Services|check factual claims]] made by media outlets. Consult these services regularly to assess the accuracy of the information you are receiving. '''3. Reflect on Your Biases''' * Recognize how your own cognitive biases may affect your interpretation of information. Strive to remain objective and open to evidence-based arguments. == Assignment == # Study the [[Evaluating Journalism Standards#Responsible Journalism Standards|Responsible Journalism Standards]] section of the Wikiversity course [[Evaluating Journalism Standards|Evaluating Journalism Standards.]] # Determine if the content you are reading meets these standards for accuracy and objectivity. # Favor content provided by reliable sources. The [[w:Wikipedia:Reliable_sources|Wikipedia policy on Reliable Sources]] provides helpful guidance.   # Complete the Wikiversity course [[Navigating Social Proof]]. #* Navigate Social Proof accurately. # Complete the Wikiversity course [[Evaluating Evidence]]. #* Evaluate evidence accurately. # Complete the Wikiversity course [[Knowing How You Know]]. #* Know how you know. # Complete the Wikiversity course [[Seeking True Beliefs]] #* Seek True Beliefs == Assignment == Three [[w:Heuristic|heuristics]], called [[w:Philosophical_razor|razors]], can help evaluate and cast doubt on various conspiracy theories. Apply each of these three razors to assess the credibility of any proposed [[w:Conspiracy_theory|conspiracy theory]] and use them to cut through the nonsense. # [[w:Occam's_razor|Occam’s razor]]—paraphrased as “The simplest explanation is usually the best one”—is a problem-solving principle that recommends searching for explanations constructed with the smallest possible set of elements. # [[w:Hanlon's_razor|Halon’s razor]] states: “Never attribute to malice that which is adequately explained by stupidity.” # Hitchens’s razor states: “What can be asserted without evidence can also be dismissed without evidence.” == Conclusion == In an era of information abundance, separating fact from fiction is both a challenge and a necessity. By understanding the characteristics of accurate, factual, representative, and objective information, individuals can build a foundation for credible knowledge. Recognizing propaganda tactics, fostering skepticism, and developing digital literacy skills empower us to navigate misinformation and disinformation effectively. The pursuit of truth demands vigilance, critical thinking, and a commitment to verifying what we consume and share. Only by cultivating these habits can we ensure that our decisions and beliefs are informed by fact, not fiction. == Further Reading == Students wishing to learn more about evaluating information may be interested in reading the following books: *{{cite book |last=Wilson |first=Edward Osborne |date=March 30, 1999 |title=Consilience: The Unity of Knowledge |publisher=Vintage |pages=384 |isbn=978-0679768678 |author-link=w:E._O._Wilson }} *{{cite book |last=Pinker |first= Steven |author-link=w:Steven_Pinker|date= September 28, 2021 |title=[[w:Rationality_(book)| Rationality: What It Is, Why It Seems Scarce, Why It Matters]]| publisher= Viking |pages=432 |isbn= 978-0525561996 }} *{{cite book |last=Frankfurt |first=Harry G. |date=January 30, 2005 |title=[[w:On_Bullshit|On Bullshit]] |publisher=Princeton University Press |pages=67 |isbn=978-0691122946 |author-link=w:Harry_Frankfurt }} *{{cite book |last=Frankfurt |first=Harry G. |date=October 31, 2006 |title=[[w:On_Truth|On Truth]] |publisher=Knopf |pages=112 |isbn=978-0307264220 |author-link=w:Harry_Frankfurt }} *{{cite book |last=Burton |first=Robert |date=March 17, 2009 |title=On Being Certain: Believing You Are Right Even When You're Not |publisher=St. Martin's Griffin |pages=272 |isbn=978-0312541521}} *{{cite book |last=Ariely |first=Dan |author-link=w:Dan_Ariely |date=September 17, 2024 |title=Misbelief: What Makes Rational People Believe Irrational Things |publisher=Harper Perennial |pages=320 |isbn=978-0063280434}} *{{cite book |last=Wolpert |first=Lewis |date=July 17, 2008 |title=Six Impossible Things Before Breakfast: The Evolutionary Origins of Belief |publisher=W. W. Norton & Company |pages=256 |isbn=978-0393332032 }} *{{cite book |last=Sunstein |first=Cass R. |date=December 23, 2014 |title=Wiser: Getting Beyond Groupthink to Make Groups Smarter |publisher=Harvard Business Review Press |pages=272 |isbn=978-1422122990 |author-link=w:Cass_Sunstein }} *{{cite book |last1=Tavris |first1=Carol |last2=Aronson |first2=Elliot |date=October 20, 2015 |title=Mistakes Were Made (but Not by Me): Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts |publisher=Mariner Books |pages=400 |isbn= 978-0544574786}} * {{Cite book|title=On freedom|last=Snyder|first=Timothy|author-link=w:Timothy_D._Snyder|date= September 17, 2024|publisher=Crown|isbn=978-0-593-72872-7|edition=First edition|location=New York}} *{{cite book |last=Haidt |first=Jonathan |date=February 12, 2013 |title=[[w:The_Righteous_Mind|The Righteous Mind: Why Good People Are Divided by Politics and Religion]] |publisher=Vintage |pages=528 |isbn=978-0307455772 |author-link=w:Jonathan_Haidt }} *{{cite book |last=Andersen |first=Kurt |date=September 5, 2017 |title=Fantasyland: How America Went Haywire: A 500-Year History |publisher=Random House |pages=480 |isbn=978-1400067213 |author-link=w:Kurt_Andersen }} *{{cite book |last=McIntyre |first=Lee |date=February 16, 2018 |title=Post-Truth |publisher=The MIT Press |pages=240 |isbn=978-0262535045 }} *{{cite book |last1=Tsipursky |first1=Gleb |last2=Ward |first2=Tim |date=May 29, 2020 |title=Pro Truth: A Practical Plan for Putting Truth Back Into Politics |publisher=Changemakers Books |page=271 |isbn=978-1789043990}} *{{cite book |last=Wilczek |first=Frank |author-link=w:Frank_Wilczek |date=January 12, 2021 |title=Fundamentals: Ten Keys to Reality |publisher=Penguin Press |pages=272 |isbn=978-0735223790}} *{{cite book |last=Galef |first=Julia |author-link=w:Julia_Galef|date=April 13, 2021 |title=The Scout Mindset: Why Some People See Things Clearly and Others Don't |publisherPortfolio |pages=288 |isbn=978-0735217553}} *{{cite book |last=Rosling |first=Hans |date=April 3, 2018 |title=Factfulness: Ten Reasons We're Wrong About the World--and Why Things Are Better Than You Think |publisher=Flatiron Books |pages=341 |isbn=978-1-250-10781-7 |author-link=w:Hans_Rosling }} *{{Cite book|title=The sirens' call: how attention became the world's most endangered resource|last=Hayes|first=Christopher|date=2025|publisher=Penguin Press|isbn=978-0-593-65311-1|location=New York}} I have not yet read the following books, but they seem interesting and relevant. They are listed here to invite further research. * Verified: How to Think Straight, Get Duped Less, and Make Better Decisions about What to Believe Online, by Mike Caulfield * The Made-Up Mind: The Meaning of Error in an Age of Certainty: Adventures in the Margin of Error, by Kathryn Schultz (Paperback) == References == <references/> [[Category:Life skills]] [[Category:Applied Wisdom]] [[Category:Philosophy]] [[Category:Clear Thinking]] [[Category:Courses]] [[Category:Reality]] [[Category:Information literacy]] {{CourseCat}} {{Clear Thinking}} ne900zkfcmux21q0anbwp4mrrbsg8yt 0 321799 2835430 2790855 2026-10-02T03:14:27Z James500 297601 /* */ Add 2835430 wikitext text/x-wiki {{Bibliography}} This part of the [[Universal Bibliography]] is a bibliography of nostalgia and retro. *The Routledge Handbook of Nostalgia [https://books.google.co.uk/books?id=EYgYEQAAQBAJ&pg=PA1977#v=onepage&q&f=false] *David Berry. On Nostalgia. 2020. [https://books.google.co.uk/books?id=U9TXDwAAQBAJ&pg=PP1#v=onepage&q&f=false] *Exploring Nostalgia: Sad, Bad, Mad and Sweet. 2016. [https://books.google.co.uk/books?id=4dweEAAAQBAJ&pg=PR1#v=onepage&q&f=false] *Illbruck. Nostalgia: Origins and Ends of an Unenlightened Disease. 2012. [https://books.google.co.uk/books?id=tlmihfXbud8C&pg=PP1#v=onepage&q&f=false] *McMahon, "Nostalgia".Kammen and Prendergast (eds). Encyclopedia of Local History. 2000. [https://books.google.co.uk/books?id=nf_M9vqUMLYC&pg=PA348#v=onepage&q&f=false p 348]. *Boym. The Future Of Nostalgia. 2001. [https://books.google.com/books?id=WrvtAAAAMAAJ] *Cassin. Nostalgia: When are We Ever at Home? 2016. [https://books.google.co.uk/books?id=yhNPyQEACAAJ] *Jacobsen (ed). Nostalgia Now: Cross-Disciplinary Perspectives on the Past in the Present. 2020. [https://books.google.co.uk/books?id=eaPSDwAAQBAJ&pg=PA1983#v=onepage&q&f=false] *Jacobsen (ed). Intimations of Nostalgia: Multidisciplinary Explorations of an Enduring Emotion. 2022. [https://books.google.co.uk/books?id=LpxKEAAAQBAJ&pg=PR1#v=onepage&q&f=false] *Gandini. Zeitgeist Nostalgia: On Populism, Work and the ‘Good Life’. 2020. [https://books.google.co.uk/books?id=hrICEAAAQBAJ&pg=PA1#v=onepage&q&f=false] *Howard, "Nostalgia" (2012) 72 Analysis 641 [https://www.jstor.org/stable/23359115] *Wilson, "Remember When: A Consideration of the Concept of Nostalgia" (1999) 56 ETC: A Review of General Semantics 296 [https://www.jstor.org/stable/42705763] *Becker, "The Meanings of Nostalgia" (2018) 57 History and Theory 234 [https://www.jstor.org/stable/26650760] *Chrostowska, "Consumed by Nostalgia?" (2010) 39 SubStance 52 [https://www.jstor.org/stable/40801075] *Cross. Consumed Nostalgia: Memory in the Age of Fast Capitalism. 2015. [https://books.google.co.uk/books?id=EyVBCgAAQBAJ&pg=PA1848#v=onepage&q&f=false] History *Shaw and Chase. The Imagined Past: History and Nostalgia. 1989. [https://books.google.co.uk/books?id=vNNRAQAAIAAJ&pg=PP1#v=onepage&q&f=false] *Becker. Yesterday: A New History of Nostalgia. 2023. [https://books.google.co.uk/books?id=OGnQEAAAQBAJ&pg=PP1#v=onepage&q&f=false]. Reviews: [https://www.newyorker.com/magazine/2023/11/27/yesterday-a-new-history-of-nostalgia-tobias-becker-book-review] [https://www.washingtonpost.com/books/2024/11/01/yesterday-tobias-becker-nostalgia-agnes-arnold-forster-invention-prehistory-stefanos-geroulanos/] *Woods. Rule, Nostalgia: A Backwards History of Britain. 2023. [https://books.google.co.uk/books?id=pmw9EAAAQBAJ&pg=PA1891#v=onepage&q&f=false] *Arnold-Foster. Nostalgia: A History of a Dangerous Emotion. 2024. [https://books.google.co.uk/books?id=11jOEAAAQBAJ&pg=PP1#v=onepage&q&f=false] *Lyon and Walsham. Nostalgia in the Early Modern World: Memory, Temporality, and Emotion. 2023. [https://books.google.co.uk/books?id=j2i5EAAAQBAJ&pg=PP1#v=onepage&q&f=false] *Austin. Nostalgia in Transition, 1780-1917. 2007. [https://books.google.co.uk/books?id=Gl_gVlQdjfQC&pg=PP1#v=onepage&q&f=false] *Landwehr, "Nostalgia and the Turbulence of the Times" (2018) 57 History and Theory 251 [https://www.jstor.org/stable/26650761] *Brandt. "A Short Natural History of Nostalgia". The Atlantic. December 1978. p 58. [https://www.theatlantic.com/magazine/archive/1978/12/a-short-natural-history-of-nostalgia/662384/] *"Local history as productive nostalgia? Change, continuity and sense of place in rural England" (2017) 18 Social & Cultural Geography 466 [https://www.tandfonline.com/doi/abs/10.1080/14649365.2016.1189591] During the Victorian period *Colley. Nostalgia and Recollection in Victorian Culture. 1998. [https://books.google.co.uk/books?id=uaGHDAAAQBAJ&pg=PP1#v=onepage&q&f=false] During the 1970s and 1980s *Dwyer. Back to the Fifties: Nostalgia, Hollywood Film, and Popular Music of the Seventies and Eighties. 2015. [https://books.google.co.uk/books?id=FMj9CAAAQBAJ&pg=PP1#v=onepage&q&f=false] *Alpers. Happy Days: Images of the Pre-Sixties Past in Seventies America. 2024. [https://books.google.co.uk/books?id=Hw3zEAAAQBAJ&pg=PA1955#v=onepage&q&f=false] *Charles Foley. "Won Ton Kong" in "Nostalgia". vol 98. [[w:The Bulletin (Australian periodical)|The Bulletin]]. No 4996: 28 February 1976. [https://nla.gov.au/nla.obj-1447552086/view?sectionId=nla.obj-1649882164&partId=nla.obj-1447711387#page/n78/mode/1up/ p 79]. *John Culhane, "Nostalgia", Newsweek, [https://books.google.co.uk/books?id=PeDjAAAAMAAJ vol 76], 28 December 1970, pp 34 to 38. ("The Old in Vogue"). *"Everybody's Just Wild About . . . Nostalgia. Life. 19 February 1971. [https://books.google.co.uk/books?id=3lMEAAAAMBAJ&pg=PP1#v=onepage&q&f=false] For the 1980s *Reliving the '80s: Nostalgic implementation of the '80s pop music in the media. University of Nevada. 2006. Thesis. [https://digitalscholarship.unlv.edu/rtds/1946/] Geography *Bonnett. The Geography of Nostalgia: Global and Local Perspectives on Modernity and Loss. 2016. [https://books.google.co.uk/books?id=ceZWCgAAQBAJ&pg=PP1#v=onepage&q&f=false] Anthropology *Angé and Berliner. Anthropology and Nostalgia. 2015. [https://books.google.co.uk/books?id=YCQfAwAAQBAJ&pg=PR3#v=onepage&q&f=false] Sociology *Fred Davis. Yearning for Yesterday: A Sociology of Nostalgia. 1979. [https://books.google.com/books?id=3zt-AAAAMAAJ] *DaSilva and Faught, "Nostalgia: A sphere and process of contemporary ideology" (1982) 5 Qualitative Sociology 47 [https://link.springer.com/article/10.1007/BF01006418] Media *Niemeyer. Media and Nostalgia: Yearning for the Past, Present and Future. 2014. [https://books.google.co.uk/books?id=7SKvAwAAQBAJ&pg=PP1#v=onepage&q&f=false] *Lizardi. Mediated Nostalgia: Individual Memory and Contemporary Mass Media. 2015. [https://books.google.co.uk/books?id=fKeDBQAAQBAJ&pg=PP1#v=onepage&q&f=false] Film and television *Leggatt. Was It Yesterday?: Nostalgia in Contemporary Film and Television. 2021. [https://books.google.co.uk/books?id=wZf1DwAAQBAJ&pg=PA1962#v=onepage&q&f=false] *Sperb. Flickers of Film: Nostalgia in the Time of Digital Cinema. 2016. [https://books.google.co.uk/books?id=o9D-CgAAQBAJ&pg=PP1#v=onepage&q&f=false] *Sprengler. Screening Nostalgia: Populuxe Props and Technicolor Aesthetics in Contemporary American Film. 2009. [https://books.google.co.uk/books?id=jCkToFfwOrsC&pg=PP1#v=onepage&q&f=false] *Furnish. Nostalgia in Jewish-American Theatre and Film, 1979-2004. 2005. [https://books.google.co.uk/books?id=treeol9deZ8C&pg=PP1#v=onepage&q&f=false] *Czach and Loiselle. Cinema of Pain: On Quebec's Nostalgic Screen. 2020. [https://books.google.co.uk/books?id=h-nyDwAAQBAJ&pg=PA1971#v=onepage&q&f=false] *Pallister (ed). Netflix Nostalgia: Streaming the Past on Demand. 2019. [https://books.google.co.uk/books?id=9DaQDwAAQBAJ&pg=PP1#v=onepage&q&f=false] *Armbruster. Watching Nostalgia: An Analysis of Nostalgic Television Fiction and its Reception. 2016. [https://books.google.co.uk/books?id=EidTDQAAQBAJ&pg=PP1#v=onepage&q&f=false] *Bevan. The Aesthetics of Nostalgia TV: Production Design and the Boomer Era. 2019. [https://books.google.co.uk/books?id=5J98DwAAQBAJ&pg=PP1#v=onepage&q&f=false] Radio and television *Punch. 3 December 1969. [https://books.google.co.uk/books?id=oXAgAQAAMAAJ] **"Nostalgia note". Evening Times. 3 December 1969. [https://books.google.co.uk/books?id=4Sw-AAAAIBAJ&pg=PA3#v=onepage&q&f=false p 4]. Literature *Łaszkiewicz, Maszewski and Partyka. Dwelling in Days Foregone: Nostalgia in American Literature and Culture. 2016. [https://books.google.co.uk/books?id=WTP5DAAAQBAJ&pg=PP1#v=onepage&q&f=false] *Ladino. Reclaiming Nostalgia: Longing for Nature in American Literature. 2012. [https://books.google.co.uk/books?id=3uGMgcG12V0C&pg=PA1#v=onepage&q&f=false] *Trilling. The Aesthetics of Nostalgia: Historical Representation in Old English Verse. 2009. [https://books.google.co.uk/books?id=HALmDQAAQBAJ&pg=PP1#v=onepage&q&f=false] Marketing *Pichierri. Nostalgia Marketing: Rekindling the Past to Influence Consumer Choices. 2023. [https://books.google.co.uk/books?id=ylazEAAAQBAJ&pg=PR1#v=onepage&q&f=false] *Tina Kießling. Nostalgie und Retro-Trends als Marketingchance. 2012. [https://books.google.co.uk/books?id=GHsQmsQWfhEC&pg=PP1#v=onepage&q&f=false] *Moriarty and McGann, "Nostalgia and Consumer Sentiment" (1983) 60 Journalism Quarterly 81 [https://journals.sagepub.com/doi/abs/10.1177/107769908306000113] Nostalgia industry *"Selling Nostalgia Is Big Business". Reading Eagle. 11 March 1962. [https://books.google.co.uk/books?id=2BMrAAAAIBAJ&pg=PA14#v=onepage&q&f=false p 14]. From Associated Press. Cf. [https://books.google.co.uk/books?id=fKEtAAAAIBAJ&pg=PA18#v=onepage&q&f=false][https://books.google.co.uk/books?id=8BYfAAAAIBAJ&pg=PA9#v=onepage&q&f=false] *Hal Boyle. "Hobbyist Saloonkeeper Is Relectant Success". Prescott Evening Courier. 11 August 1959. [https://books.google.co.uk/books?id=gy1PAAAAIBAJ&pg=PA3#v=onepage&q&f=false p 4]. From Associated Press. Cf [https://books.google.co.uk/books?id=dt9NAAAAIBAJ&pg=PA3#v=onepage&q&f=false] [https://books.google.co.uk/books?id=rSATAAAAIBAJ&pg=PA12#v=onepage&q&f=false]. Politics *Quill. Nostalgia and Political Theory. 2024. [https://books.google.co.uk/books?id=9aroEAAAQBAJ&pg=PA1#v=onepage&q&f=false] *Tanner. The Hours Have Lost Their Clock: The Politics of Nostalgia. 2021. [https://books.google.co.uk/books?id=d9ATEAAAQBAJ&pg=PA1#v=onepage&q&f=false] *Bonnett. Left in the Past: Radicalism and the Politics of Nostalgia. 2010. [https://books.google.co.uk/books?id=e8WoAwAAQBAJ&pg=PP1#v=onepage&q&f=false] *Campanella and Dassù. Anglo Nostalgia: The Politics of Emotion in a Fractured West. 2019. [https://books.google.co.uk/books?id=iaCgDwAAQBAJ&pg=PP1#v=onepage&q&f=false] Childhood *Wesseling (ed). Reinventing Childhood Nostalgia: Books, Toys, and Contemporary Media Culture. 2017. [https://books.google.co.uk/books?id=bu80DwAAQBAJ&pg=PA1#v=onepage&q&f=false] Psychology *Routledge. Nostalgia: A Psychological Resource. 2016. [https://books.google.co.uk/books?id=6dyoCgAAQBAJ&pg=PP1#v=onepage&q&f=false] *"Nostalgia: Past, Present, and Future" (2008) 17 Current Directions in Psychological Science 304 [https://www.jstor.org/stable/20183308] *Daniels, "Nostalgia and Hidden Meaning" (1985) 42 American Imago 371 [https://www.jstor.org/stable/26303822] Medical *Dodham. What Nostalgia Was: War, Empire, and the Time of a Deadly Emotion. [https://books.google.co.uk/books?id=VxNDDwAAQBAJ&pg=PP1#v=onepage&q&f=false] Retro *Guffey. Retro: The Culture of Revival. 2006. [https://books.google.co.uk/books?id=2d8J08XNdKEC&pg=PP1#v=onepage&q&f=false] *Reynolds. Retromania: Pop Culture's Addiction to its Own Past. 2011. [https://books.google.co.uk/books?id=0Hgtu9Zwok0C&pg=PA2001#v=onepage&q&f=false] *Brown. Marketing - The Retro Revolution. 2001. [https://books.google.co.uk/books?id=H5G3rOh-VDkC&pg=PP1#v=onepage&q&f=false] Vicarious nostalgia *"Missing Someone Else's Past". Psychology Today. 30 January 2013. [https://www.psychologytoday.com/gb/blog/longing-for-nostalgia/201301/missing-someone-elses-past] *"Effects of advertising-evoked vicarious nostalgia on brand heritage" (2013) 66 Journal of Business Research 2619 [https://www.sciencedirect.com/science/article/abs/pii/S0148296312001737] *"Reminiscing Other People’s Memories: Conceptualizing and Measuring Vicarious Nostalgia Evoked by Heritage Tourism" (2020) 61 Journal of Travel Research [https://journals.sagepub.com/doi/10.1177/0047287520969904] *"Antecedents of tourism vicarious nostalgia". Tourism, Change and the Global South. [https://books.google.co.uk/books?id=jD4qEAAAQBAJ&newbks=1&newbks_redir=0&lpg=PA2006&pg=PA2006#v=onepage&q&f=false Chapter 4]. United States *Sayers. The Promise of Nostalgia: Reminiscence, Longing and Hope in Contemporary American Culture. 2020. [https://books.google.co.uk/books?id=BSnJDwAAQBAJ&pg=PP1#v=onepage&q&f=false] [[Category:Culture]] i6sbmj7qvver4ac9km7t6z3zn2khbub 0 322486 2835367 2785064 2026-10-01T17:04:52Z D.H 52339 /* Lorentz (1914) */ 2835367 wikitext text/x-wiki {| style="width:20%; font-size:13px;" align=right |{{../Other Topics (header)}} |} ==Early history of the Penrose–Terrell effect== {{Lorentzbox|Text={{center|Date of article creation: 19 July 2025; Last major revision: 12 December 2025}}}} If the length of an object is measured exactly at the locations of its endpoints, then its [[w:rest length]] <math>l'</math> is related to its length <math>l</math> in a relatively moving frame by the [[w:length contraction]] formula: :(1) <math>\quad l=l'\sqrt{1-v^{2}/c^{2}}</math> However, it turns out that the ''visual appearance'' of that object when photographed from a distance leads to quite different results, because optical aberration and time-of-flight effects have to be considered as well. In particular, light rays arriving simultaneously at the camera weren't emitted simultaneously from all locations at the source.<ref group=S name=space>A very detailed account of the visual appearance of moving bodies is presented on the website [https://www.spacetimetravel.org/ Space Time Travel] which is based on the German website [https://www.tempolimit-lichtgeschwindigkeit.de/ Tempolimit Lichtgeschwindigkeit], where the accompanied paper [https://www.tempolimit-lichtgeschwindigkeit.de/phantom/pdnw97.pdf Appearance of relativistically moving objects (in German)] gives the formula for the length of 1D rods, followed by descriptions of rotated cubes and spheres.</ref> ;1D rods The visual length <math>L</math> of a 1D rod that is both oriented and moving ''along'' the x-axis, and which approaches or recedes a camera that is located on the same x-axis, is given by :(2) <math>\quad\begin{matrix}L_{{\rm approach}}=\frac{l}{1-v/c}=l'\sqrt{\frac{1+v/c}{1-v/c}}\\ L_{{\rm recede}}=\frac{l}{1+v/c}=l'\sqrt{\frac{1-v/c}{1+v/c}} \end{matrix}</math> So if the 1D rod approaches it appears to be longer, if it recedes it appears to be shorter, and none of those lengths precisely matches the contraction formula (1) but rather depend on the [[w:Relativistic_Doppler_effect|w:relativistic Doppler factor]] that also appears in the [[w:Aberration (astronomy)#Relativistic explanation|w:relativistic aberration formula]]. {{Lorentzbox|Text=Formula (2) was introduced by {{section link||Petzoldt (1914)}} and in a more general way that also allows for motions along lines ''parallel'' to the x-axis by {{section link||Lorentz (1914)|Lampa (1924)}}. Even before those authors, the visual position of a ''point'' was derived by {{section link||Mangoldt (1910)}} and related to photographic images by {{section link||Grünbaum (1911)}}.}} The visual length on a photograph ''directly'' corresponds to contraction formula (1) when the moving 1D rod is oriented ''perpendicular'' to the camera's line of sight and the rod's center is exactly in the camera's line of sight at the time of light emission, because in this case the light emanating ''simultaneously'' from both ends of the moving rod will travel the same distance to the camera and therefore arrive ''simultaneously'' as well, which can be compared to the visual length of a stationary rod that was momentarily at the same position as the moving rod when light was emanated from its endpoints. {{Lorentzbox|Text=This was demonstrated by {{section link||Lorentz (1922)}}.}} In case the rod's center is ''not'' exactly in the camera's line of sight at the time of light emission, Lorentz contraction can only be detected on photographs by resorting to approximations such as making the rod's length very small with respect to the rod's distance from the camera. {{Lorentzbox|Text=This was shown by {{section link||Mangoldt (1910)|Grünbaum (1911)|Lorentz (1914)}}.}} ;3D objects It becomes more complicated when 3D objects are considered. First we notice the conformal property of the [[w:Aberration (astronomy)#Relativistic explanation|w:relativistic aberration formula]] :(3) <math>\quad\tan\frac{\phi}{2}=\sqrt{\frac{1+v/c}{1-v/c}}\tan\frac{\phi'}{2}</math> because it only changes the scale but not the shape of spherical outlines, thus the visual appearance of spheres ''remains spherical'' on camera. {{Lorentzbox|Text=This was pointed out by {{section link||Plummer (1910)}} and rediscovered by {{section link||Penrose (1958/59) and Terrell (1959)}}.}} Furthermore, light emitted on the backside of arbitrary 3D objects such as spheres, rods and cubes can reach the camera, because the object's motion frees the path of light rays that were hidden otherwise. Consequently, if the object is very far away and subtends a very small angle, it doesn't appear contracted but rather ''rotated'' by <math>\phi-\phi'</math>. {{Lorentzbox|Text=This was pointed out by {{section link||Penrose (1958/59) and Terrell (1959)}}.}} The description of visual distortions is connected to the names of Penrose and Terrell in most papers, hence it is called [[w:Penrose–Terrell effect]]/rotation or Terrell effect/rotation or Lampa–Penrose–Terrell effect. Given the historical information provided above, the expression '''Penrose-Terrell effect''' is appropriate when it comes to rotations alone; yet when it comes to the visual appearance of moving bodies in general, one should should not forget the early contributions of Plummer, Petzoldt, Lorentz, Lampa. ==Historical papers== ===Plummer (1910)=== [[w:Henry Crozier Keating Plummer]]<ref name=plum10 /> derived the following consequence from relativistic aberration: :In the first place we may consider the stereographic projection of the celestial sphere on the tangent plane perpendicular to the direction of motion. The form of the law of aberration ::<math>\tan\frac{1}{2}\phi'=\sqrt{\frac{U-v}{U+v}}\tan\frac{1}{2}\phi</math> :shows that the effect of aberration is simply to alter the ''scale'' of the projection. But the stereographic projection is a conformal representation of the sphere. Hence actual configurations on the sphere are only changed conformally by the effect of aberration, or in other words any small area is altered only in size and not in shape. We know that aberration merely changes the scale of a photograph of a small part of the sky, and the truth of this fact now becomes independent of the velocity (however large) of the observer. Also stars which appear to lie on a circle at any one time will continue to do so permanently. {{Lorentzbox|Text=Thus Plummer showed that independent of the velocity of the observer, the ''photograph'' of parts of the celestial sphere is changed by relativistic aberration only in terms of scale, not shape, thus spherical outlines remain spherical.}} ===Mangoldt (1910)=== [[w:Hans Carl Friedrich von Mangoldt]]<ref name=mang10 /> demonstrated the constancy of light speed in different frames by using the case of a light ray emitted from the origin and then traversing distance <math>-l</math> in the negative x-direction during time <math>t=l/c</math>. A ''moving'' marker momentarily co-located at position <math>-l</math> at time <math>t</math> will indicate the Lorentz transformed value :<math>x'=\beta(x-vt)=-\beta\left(l+v\frac{l}{c}\right)=-\beta l\left(1+\frac{v}{c}\right)</math> and a momentarily co-located moving clock indicates :<math>t'=\beta\left(-\frac{v}{c^{2}}x+t\right)=\beta\left(\frac{v}{c^{2}}l+\frac{l}{c}\right)=\beta\frac{l}{c}\left(1+\frac{v}{c}\right)</math> where <math>\beta=1/\sqrt{1-v^{2}/c^{2}}</math> was used by him as Lorentz factor, proving <math>x'/t'=-c</math> as it should be. At the end of his paper, he alluded to the possibility of using ''photographs'' of ''sufficiently small areas'' at ''sufficient distance'' from the camera, which should directly provide an ''approximately'' correct image of relativistic effects such as length contraction and time dilation as indicated by markers and clocks. {{Lorentzbox|Text=a) We see that his position equation that incorporates the time-of-flight of light (using modern notation <math>\gamma</math> for the Lorentz factor) :<math>x'=-\gamma l\left(1+\frac{v}{c}\right)=l\sqrt{\frac{1+v/c}{1-v/c}}</math>, is formally equivalent to equation (2), and it's easy to re-interpret his result in terms of visual lengths: We introduce a rod whose rest length <math>l'</math> is defined by coordinate <math>x'</math> as left endpoint and the origin as right endpoint, in which case Mangoldt's distance <math>l</math> is identical with the rod's visual length <math>L</math> as photographed at time <math>t=l/c</math> by a camera located at position <math>-l</math>. b) Ironically, even though he was in possession of the optical position formula that incorporates the time-of-flight of light, he only discussed an ''approximate'' case in order to directly demonstrate length contraction and time dilation on photographic images ''without'' considering time-of-flight delays, which was clarified by {{section link||Grünbaum (1911)}}. Anyway, Mangoldt's restriction to an approximate case shows, that he was well aware that an exact treatment requires the consideration of time-of-flight delays.}} ===Grünbaum (1911)=== In a follow-up paper to {{section link||Mangoldt (1910)}}, the physicist [[w:de:Fritz Grünbaum (Physiker)|w:Fritz Grünbaum]]<ref name=gbaum /> discussed the ''photographic image'' of distant points. He described a marker (indicating its spatial position) and a co-located clock (indicating its time) that are at relative rest with respect to a photographic apparatus, and another marker/clock pair in relative motion with respect to that apparatus. When both marker/clock pairs meet each other at point P, the apparatus located at point R makes a photo of them. In the rest frame of the apparatus, <math>l</math> is the distance from P to R, and T is the time at which the image was created on the photographic plate. On that image, the resting marker indicates its spatial coordinate <math>x_{r}</math> while the resting clock indicates its time <math>t_{r}=T-l/c</math> since light took some time to traverse distance <math>l</math>. In order to find out which values are indicated on the photographic image of the ''moving'' marker/clock pair, he used the Lorentz transformation (with <math>\beta</math> as Lorentz factor): :<math>\begin{matrix}x'_{r}=\beta\left(x_{r}-vt_{r}\right)\Rightarrow\beta\left[x-v\left(T-\frac{l}{c}\right)\right]\\ t'_{r}=\beta\left(t_{r}-\frac{v}{c^{2}}x_{r}\right)\Rightarrow\beta\left[\left(T-\frac{l}{c}\right)-\frac{v}{c^{2}}x\right]\\ \left[\beta=\frac{1}{\sqrt{1-v^{2}/c^{2}}},\ x_{r}=x,\ t_{r}=T-\frac{l}{c}\right] \end{matrix}</math> which he summarized in the following table: {| cellpadding="10" |- |On the image <br />of the apparatus: |style="border-left:1px solid black" |Stationary marker: <math>x,\ y=0</math> Stationary clock: <math>T-\frac{l}{c}</math> Moving marker: <math>\beta\left[x-v\left(T-\frac{l}{c}\right)\right]</math> Moving clock: <math>\beta\left[\left(T-\frac{l}{c}\right)-\frac{v}{c^{2}}x\right]</math> |} He then described the symmetrical case when the photographic image of P is made by a ''moving'' observer B, discussed the special cases <math>T=T'=0</math> , which together with <math>x=0</math> and <math>l=y</math> and by considering time-of-flight effects, allows to indirectly recover both length contraction and time dilation as well as their symmetry by analyzing the data given on the images. Finally he clarified Mangoldt's claim according to whom one can directly demonstrate length contraction ''without'' considering time-of-flight effects: He showed that this can only be done if one strictly follows Mangoldt's requirement that the rod length <math>x</math> must be very small compared to distance <math>y</math>, which indeed produces the Lorentz contraction formula <math>x'=\beta x</math> because the differences in the emission times at the endpoints are so small that they approximately happened simultaneously. {{Lorentzbox|Text=a) His formula for the visual ''position'' of a ''photographed'' marker in motion easily allows us to derive the visual ''length'' between two points: We place R to the origin <math>x_{0}=0</math> so that point P is at position <math>x=l</math>, thus we can interpret R and P as endpoints of a horizontally aligned and moving rod measured at time <math>T=0</math>, which gives (using modern notation <math>\gamma</math> for the Lorentz factor): :<math>x'_{r}=\gamma\left[x-v\left(T-\frac{l}{c}\right)\right]\underset{{x=l\atop T=0}}{=}\gamma\left[l-\frac{v}{c}l\right]=l\sqrt{\frac{1-v/c}{1+v/c}}</math> equivalent to equation (2) by identifying his length <math>l</math> with visual length <math>L</math> and coordinate <math>x'_{r}</math> as the right endpoint of a rod of rest length <math>l'</math> whose left endpoint is at the origin. So Grünbaum correctly incorporated time-of-flight effects in order to derive the visual ''position'' of points with respect to photographs. Yet he treated the visual ''length'' of moving rods only in approximation while clarifying Mangoldt's statements. b) In a short review of Grünbaum's paper, [[w:Max von Laue]] (1911)<ref name=laue11gru /> described it as using photographic images to demonstrate Lorentz contraction. }} ===Petzoldt (1914)=== In an otherwise philosophical analysis of relativity, [[w:Joseph Petzoldt]]<ref name=petz /> demonstrated the following consequence: :The perspectivistic shape changes of bodies whose velocity is comparable to that of light, do not appear to have been investigated yet. [..] The image of an object, which is generated on the retina of the eye or on the photographic plate - as a snapshot - is produced by light coming from all the points of the object in question, but it wasn't sent at the same time: all of the light that contributes to the production of the image arrives simultaneously with the light that originated from those points of the object that were closest to the eye or plate; the further the object's point is from the plate or eye, the sooner it must send its contribution of light. The result is that the image of a receding or approaching object having a large speed comparable to that of light, does not correspond to the image of the same object if it were at rest relative to the eye or plate, but rather gives the impression that it originated from a shorter or longer object within that radius of distance. In case the object is receding from the eye or plate, the light contributed from the most distant points would have been sent later, in the case of approach it would have been sent earlier than in the state of rest. A simple calculation that takes into account the Lorentz contraction, results in the fact that the object in question whose physical length is <math>l\sqrt{1-\tfrac{v^{2}}{c^{2}}}</math>, where <math>l</math> is the length for the "co-moving" observer, would have to be assessed on the basis of this photographic momentary image as having the perspectivistic moving length: ::<math>l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c+v}\qquad</math> or <math>\qquad l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c-v}</math>, :depending on the whether the object recedes or approaches the eye or plate. {{Lorentzbox|Text=a) Petzoldt correctly derived the visual length of moving 1D rods, his results being equivalent to equation (2): :<math>\begin{matrix}l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c-v}=l\sqrt{\frac{1+v/c}{1-v/c}}\\ l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c+v}=l\sqrt{\frac{1-v/c}{1+v/c}} \end{matrix}</math> b) As explained in [[w:Joseph Petzoldt|Petzoldt's Wikipedia article]], it was [[w:Albert Einstein]] himself who publicly recommended Petzoldt's 1914 paper in a newspaper article and privately praised it by letter, which implies that by 1914, Einstein should have been aware of the pitfalls that arise when describing photographs of Lorentz contracted bodies. However, in the [[s:Relativity (1931)/Appendix 1|s:first appendix]] to his popular book [[w:Relativity: The Special and the General Theory]] that was added to the third edition from 1918 and still remains in modern editions,<ref name=einst17pop /> he seems to have overlooked this fact. Einstein argued that <math>\Delta x=1/a</math> is the length indicated on a "snapshot" or "instantaneous photograph" of a unit length at rest in K' that was taken from system K at time <math>t=0</math>, and that <math>\Delta x'=a\left(1-v^{2}/c^{2}\right)</math> is the length indicated on a snapshot of a unit length at rest in K that was taken from system K' at time <math>t'=0</math>; since symmetry requires that <math>\Delta x=\Delta x'</math>, he concluded that <math>a^{2}=1/\left(1-v^{2}/c^{2}\right)</math>. If we plug his result into his snapshot length equations we get <math>\Delta x=\sqrt{1-v^{2}/c^{2}}</math> and symmetrically <math>\Delta x'=\sqrt{1-v^{2}/c^{2}}</math>, identical to the Lorentz contraction of unit rest lengths. Yet while Einstein's derivation is correct, his choice of visualizing this result in terms of "snapshots" can be misleading since one has to consider time-of-flight effects which leads to visual deviations in most cases. }} ===Lorentz (1914)=== [[File:Lorentz1914-2.png|250px|right]] [[w:Hendrik Lorentz]] (March 1914)<ref name=lorentz14 /> described two rulers along line EF, one at rest with respect to observer A having length <math>l'=l</math> and the other moving with respect to A with velocity <math>v</math> having contracted length <math>l'=l/a</math> (where <math>a</math> is the Lorentz factor). He then derived a general formula for the approximated visual length <math>s</math> of the rods as a function of <math>l'</math>, using an photographic apparatus moving with velocity <math>w</math>. On the screen of the apparatus there is a small slot D situated at vertical distance L from E, and below there is a photographic plate at vertical distance <math>\lambda</math> from D. Then slot D is opened for one moment, during which it is passed by optical signals from endpoints F and G of the rods (where <math>FG=l'</math>), reaching points f and g on the plate. Since the signals reaching D at the same time are sent from different locations, they were not emitted simultaneously. Assuming the signal from F was sent at time <math>t_{0}</math> at position <math>x_{0}</math> after which it traverses distance <math>\sqrt{L^{2}+x_{0}^{2}}</math> to D, it follows that the signal from G was sent at an earlier time <math>t_{0}+\tau</math> at position <math>x_{1}=x_{0}+l'+v\tau</math> after which it traverses distance <math>\sqrt{L^{2}+\left(x_{0}+l'+v\tau\right)^{2}}</math> to D. Thus the value of <math>\tau</math> is given by :<math>\sqrt{L^{2}+\left(x_{0}+l'+v\tau\right)^{2}}-\sqrt{L^{2}+x_{0}^{2}}=-c\tau</math> or using angle <math>EDF=\phi_{0}</math> and assuming very large L by which terms containing <math>l'^{2}</math> and <math>\tau^{2}</math> can be neglected: :<math>\tau=-\frac{\sin\phi_{0}}{c+v\sin\phi_{0}}l'</math>, thus <math>x_{1}=x_{0}+\frac{cl'}{c+v\sin\phi_{0}}</math>. After deriving the position of points f and g on the plate, and under consideration that the plate was moving with velocity <math>w</math>, he obtained the general formula representing the approximated visual length of rods: :<math>s=\frac{\lambda}{L}\frac{c+w\sin\phi_{0}}{c+v\sin\phi_{0}}l'</math>. The visual length <math>s_{1}</math> of the resting rod follows by plugging in <math>v=0</math> and <math>l'=l</math>, whereas visual length <math>s_{2}</math> of the moving rod follows by plugging in <math>l'=l/a</math> (where <math>a</math> is the Lorentz factor), thus :<math>\frac{s_{1}}{s_{2}}=\left(1+\frac{v}{c}\sin\phi_{0}\right)a</math>. He showed that the case <math>\phi_{0}=0</math> allows to recover the Lorentz contraction formula :<math>\frac{s_{1}}{s_{2}}=a</math>, which is possible because in this approximation neglecting terms containing <math>l'^{2}</math>, one can pretend as if the emission of the light signals at F and G happened simultaneously. {{Lorentzbox|Text=a) Setting <math>\phi_{0}=\pi/2</math> (i.e. 90 degrees), Lorentz's formula produces :<math>\frac{s_{1}}{s_{2}}=\left(1+\frac{v}{c}\right)a=\sqrt{\frac{1+v/c}{1-v/c}}</math> equivalent to the longitudinal visual length formula (2), independently derived by {{section link||Petzoldt (1914)}}. b) Lorentz's last case <math>\phi_{0}=0</math> agrees with {{section link||Mangoldt (1910)|Grünbaum (1911)}} who argued that Lorentz contraction can be recovered from the data on photographs under certain approximations.}} ===Lorentz (1922)=== In 1922 (published 1927),<ref name=lorentz22 /> [[w:Hendrik Lorentz]] simplified his earlier treatment of 1914 by writing: [[File:Lorentz1927-31.png|250px|right]] :Let there be two “equal” rods P and Q, placed along the line AB parallel to OZ, and let the first be at rest in x, y, z, t, the other in x’, y’, z’, t’. The screen CD coincides with the plane YOZ, the distance OK being <math>p</math>, and EF is the photographic plate, at a distance <math>OM=q</math> behind the screen. :In A’s experiment the screen and the photographic plate are at rest in the system x, y, z, the pinhole being constantly at the origin O of those coordinates. We shall suppose it to be opened for an instant at time <math>t=0</math>, and we shall define the “effective” position of a moving point by the condition that light emitted by the point in that position shall reach the hole O just when it is opened; the time at which the effective position is reached may be called the effective time. We shall denote by <math>2l</math> the length of the rod P in the system x, y, z, so that in the same system <math>2a/l</math> [with <math>a</math> as Lorentz factor] is the length of Q. For the sake of simplicity we shall suppose <math>l</math> to be so small that terms with <math>l^{2}</math> may be neglected. :Now A must be sure that he compares ''simultaneous'' positions of the ends of the moving rod Q. He can satisfy this condition by arranging the experiment in such a way that the middle point of Q passes through <math>K(z=0)</math> at the time <math>-p/c</math>. We shall further assume that the middle point of P always has this position. :It is easily seen that in this first experiment the images of the two rods have the lengths <math>2\tfrac{q}{p}l</math> and <math>2\tfrac{q}{p}\tfrac{l}{a}</math>, the second being <math>a</math> times shorter than the first. {{Lorentzbox|Text=a) Lorentz's method, in which both endpoints of the rod have the same distance to hole O, can indeed accurately represent the different lengths of resting and moving 1D rods on a photograph. b) As later shown by {{section link||Penrose (1958/59) and Terrell (1959)}}, this method doesn't work anymore when 3D objects are considered.}} ===Lampa (1924)=== [[w:de:Anton Lampa]]<ref name=Lampa /> devoted an entire paper to the question of the visual length of moving rods. He pointed out, that the relativistic length contraction formula doesn't say anything about the visual appearance of moving rods from the perspective of non-comoving observers. He started by defining a rod of rest length <math>l'</math> with endpoint coordinates <math>x'_{A}=y'_{A}=0</math> and <math>x'_{B}=l',\,y'_{B}=0</math>, letting a light signal be sent from B to the origin starting at time <math>t'_{B}=-l'/c</math> and arriving at time <math>t'=0</math>. The Lorentz transformation into another frame K which is ''moving'' parallel to the x-axis gives: :<math>\begin{align}x_{B} & =\frac{x'_{B}+vt'_{B}}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=\frac{l'-\frac{v}{c}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=l'\frac{\sqrt{1-\frac{v^{2}}{c^{2}}}}{1+\frac{v}{c}}\\ t_{B} & =\frac{t'_{B}+\frac{v}{c^{2}}x'_{B}}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=\frac{-\frac{l'}{c}+\frac{v}{c^{2}}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=-\frac{l'}{c}\frac{\sqrt{1-\frac{v^{2}}{c^{2}}}}{1+\frac{v}{c}} \end{align} </math> from which he derived the Lorentz contracted length as follows: :<math>l=x_{B}+v(0-t_{B})=x_{B}-vt_{B}=l'\sqrt{1-v^{2}/c^{2}}</math> {{Lorentzbox|Text=As in the case of {{section link||Mangoldt (1910)}}, Lampa's position formula that incorporates the time-of-flight of light :<math>x_{B}=l'\frac{\sqrt{1-v^{2}/c^{2}}}{1+v/c}=l'\sqrt{\frac{1-v/c}{1+v/c}}</math>, is equivalent to equation (2) by re-interpreting <math>x_{A}=0</math> and <math>x_{B}</math> as endpoints defining the visual length of the rod.}} In order to explicitly derive the visual length of the rod, he discussed a more general case in which the endpoints A and B of the rod at rest in frame K' are given by coordinates <math>x'_{A}=0,\,y'_{A}=y'</math> and <math>x'_{B}=l',\,y'_{B}=y'</math>. So when an observer resting at the origin sees the rod at time <math>t'=0</math> , the rod's light must have been sent earlier at time <math>t'_{A}=-y'/c</math> from A and at an even earlier time <math>t'_{B}=-\sqrt{y^{\prime2}+l^{\prime2}}/c</math> from B. Applying the Lorentz transformation, he showed that the visual distance <math>\lambda</math> between A and B seen by an observer at the origin of another frame K which is ''moving'' parallel to the x-axis, is given as follows: :<math>\lambda=x_{B}-x_{A}=\frac{l'-\frac{v}{c}\left(\sqrt{y^{\prime2}+l^{\prime2}}-y'\right)}{\sqrt{1-\frac{v^{2}}{c^{2}}}}</math> He concluded: :This distance is a function of <math>v/c</math> at given <math>l'</math> and <math>y'</math>. If <math>v=0</math> or <math>v/c=0</math>, we have <math>x_{B}=l'</math> and <math>x_{A}=0</math>, thus <math>\lambda=l'</math> as it must be, because the coordinate systems always coincide at <math>v=0</math>. If we increase <math>v/c</math> beginning with value zero, then <math>x_{B}</math> decreases and finally becomes negative, while the absolute value of <math>x_{A}</math> steadily increases; <math>x_{B}-x_{A}</math> initially decreases, then reaches a minimum and then permanently increases. If <math>v/c=l'/\sqrt{y^{\prime2}+l^{\prime2}}</math>, then <math>x_{B}=0</math> and <math>x_{A}=-l'</math> and <math>\lambda</math> becomes equal to <math>l'</math>. We see that the distance of the points from which the light rays emanate as measured in system K of the stationary observer, is not at all smaller than the length of the rod measured in the coordinate system attached to it; it even becomes infinitely large if the rod moves relative to the observer with the speed of light. Yet the visual angle under which the stationary observer sees points A and B of the rod, is always finite. In frame K, he defined <math>\alpha</math> as angle of the light ray emanating from endpoint A at time <math>t_{A}</math> and <math>\beta</math> as angle of the light ray emanating from endpoint B at time <math>t_{B}</math>, and then derived the relation between the [[w:visual angle]] <math>\varphi=\beta-\alpha</math> observed in K and angle <math>\varphi'</math> observed in K' by: :<math>\begin{matrix}\sin\varphi=\sin(\beta-\alpha)=\sin\beta\cos\alpha-\cos\beta\sin\alpha\\ \sin\varphi'=\frac{l'}{\sqrt{y^{\prime2}+l^{\prime2}}},\ \cos\varphi'=\frac{y'}{\sqrt{y^{\prime2}+l^{\prime2}}}\\ \Downarrow\\ \sin\varphi=\frac{\sin\varphi'-\frac{v}{c}(1-\cos\varphi')}{1-\frac{v}{c}\sin\varphi'}\sqrt{1-\frac{v^{2}}{c^{2}}} \end{matrix}</math> He finally showed how to recover the Lorentz contracted length <math>l</math> from visual length <math>\lambda</math>: :<math>\begin{align}l & =\lambda+v\left(t_{A}-t_{B}\right)\\ & =l'\sqrt{1-\frac{v^{2}}{c^{2}}} \end{align} </math> which he rewrote in terms of angles <math>\alpha</math> and <math>\beta</math> as: :<math>\begin{align}\lambda & =y'(\tan\beta-\tan\alpha);\quad t_{A}-t_{B}=\frac{y'}{c}\left(\frac{1}{\cos\beta}-\frac{1}{\cos\alpha}\right)\\ \Rightarrow l & =y'\left[(\tan\beta-\tan\alpha)+\frac{v}{c}\left(\frac{1}{\cos\beta}-\frac{1}{\cos\alpha}\right)\right] \end{align} </math> {{Lorentzbox|Text=a) Lampa's formula for <math>\lambda</math> is more general than equation (2), producing the latter in the special case <math>y'=0</math>: :<math>\lambda=\frac{l'-\frac{v}{c}\left(\sqrt{y^{\prime2}+l^{\prime2}}-y'\right)}{\sqrt{1-\frac{v^{2}}{c^{2}}}}\underset{y'=0}{=}\frac{l'-\frac{v}{c}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=l'\sqrt{\frac{1-v/c}{1+v/c}}</math> b) He was evidently unaware of previous work on visual positions and lengths by {{section link||Grünbaum (1911)|Petzoldt (1914)|Lorentz (1914)}}. c) In a short review of Lampa's paper, [[w:Cornelius Lanczos]] (1925)<ref name=lanc25 /> described it as deriving the relation between the visual angles of a moving rod seen by resting and moving observers, as well as deriving the length of the rod from the data of its appearance.}} ===Penrose (1958/59) and Terrell (1959)=== {{section link||Petzoldt (1914)|Lorentz (1914)|Lampa (1924)}} restricted their investigations to the visual appearance of 1D rods, whereas the only early description of the visual appearance of 3D objects was given by {{section link||Plummer (1910)}} in relation to the celestial sphere based on the conformal property of aberration. However, these early investigations were evidently completely forgotten, and it took decades before those questions were taken up again: Using the conformal property of aberration, [[w:Roger Penrose]] (1958/59)<ref name=Penrose /> described the visual appearance of spheres, and discovered a completely new effect: Due to the motion of the sphere, points that were in the background become visible due to the sphere's motion, leading to the effect that the sphere appears not to be Lorentz contracted but rather rotated. Independently, [[w:James Terrell]] (1959)<ref name=Terrell /> noticed the same rotation effect in relation to 3D rods, leading him to famously declare the "invisibility of the Lorentz contraction". Independently, the special case of the visual length of 1D rods was discussed by Weinstein (1959/60).<ref name=wein60 /> A large number of follow-up papers by many authors appeared, which demonstrate the visual appearance of 1D and 3D objects in detail, see [[w:Penrose-Terrell effect]]. ==References== ===Historical references=== <references> <ref name=plum10>{{replace|{{#section:History of Topics in Special Relativity/relsource|plum10}}|*||count=1}}</ref> <ref name=mang10>{{replace|{{#section:History of Topics in Special Relativity/relsource|mang10}}|*||count=1}}</ref> <ref name=gbaum>{{replace|{{#section:History of Topics in Special Relativity/relsource|gbaum}}|*||count=1}}</ref> <ref name=laue11gru>{{replace|{{#section:History of Topics in Special Relativity/relsource|laue11gru}}|*||count=1}}</ref> <ref name=petz>{{replace|{{#section:History of Topics in Special Relativity/relsource|petz}}|*||count=1}}</ref> <ref name=einst17pop>{{replace|{{#section:History of Topics in Special Relativity/relsource|einst17pop}}|*||count=1}}</ref> <ref name=Lampa>{{replace|{{#section:History of Topics in Special Relativity/relsource|Lampa}}|*||count=1}}</ref> <ref name=lanc25>{{replace|{{#section:History of Topics in Special Relativity/relsource|lanc25}}|*||count=1}}</ref> <ref name=Penrose>{{replace|{{#section:History of Topics in Special Relativity/relsource|Penrose}}|*||count=1}}</ref> <ref name=Terrell>{{replace|{{#section:History of Topics in Special Relativity/relsource|Terrell}}|*||count=1}}</ref> <ref name=wein60>{{replace|{{#section:History of Topics in Special Relativity/relsource|wein60}}|*||count=1}}</ref> <ref name=lorentz14>{{replace|{{#section:History of Topics in Special Relativity/relsource|lorentz14}}|*||count=1}}</ref> <ref name=lorentz22>{{replace|{{#section:History of Topics in Special Relativity/relsource|lorentz22}}|*||count=1}}</ref> </references> ===Further reading=== <references group=S /> [[Category:History of special relativity]] 4b0e6mey9xpq2l2ta6df0cvg18p9b26 2835368 2835367 2026-10-01T17:07:35Z D.H 52339 /* Lorentz (1914) */ 2835368 wikitext text/x-wiki {| style="width:20%; font-size:13px;" align=right |{{../Other Topics (header)}} |} ==Early history of the Penrose–Terrell effect== {{Lorentzbox|Text={{center|Date of article creation: 19 July 2025; Last major revision: 12 December 2025}}}} If the length of an object is measured exactly at the locations of its endpoints, then its [[w:rest length]] <math>l'</math> is related to its length <math>l</math> in a relatively moving frame by the [[w:length contraction]] formula: :(1) <math>\quad l=l'\sqrt{1-v^{2}/c^{2}}</math> However, it turns out that the ''visual appearance'' of that object when photographed from a distance leads to quite different results, because optical aberration and time-of-flight effects have to be considered as well. In particular, light rays arriving simultaneously at the camera weren't emitted simultaneously from all locations at the source.<ref group=S name=space>A very detailed account of the visual appearance of moving bodies is presented on the website [https://www.spacetimetravel.org/ Space Time Travel] which is based on the German website [https://www.tempolimit-lichtgeschwindigkeit.de/ Tempolimit Lichtgeschwindigkeit], where the accompanied paper [https://www.tempolimit-lichtgeschwindigkeit.de/phantom/pdnw97.pdf Appearance of relativistically moving objects (in German)] gives the formula for the length of 1D rods, followed by descriptions of rotated cubes and spheres.</ref> ;1D rods The visual length <math>L</math> of a 1D rod that is both oriented and moving ''along'' the x-axis, and which approaches or recedes a camera that is located on the same x-axis, is given by :(2) <math>\quad\begin{matrix}L_{{\rm approach}}=\frac{l}{1-v/c}=l'\sqrt{\frac{1+v/c}{1-v/c}}\\ L_{{\rm recede}}=\frac{l}{1+v/c}=l'\sqrt{\frac{1-v/c}{1+v/c}} \end{matrix}</math> So if the 1D rod approaches it appears to be longer, if it recedes it appears to be shorter, and none of those lengths precisely matches the contraction formula (1) but rather depend on the [[w:Relativistic_Doppler_effect|w:relativistic Doppler factor]] that also appears in the [[w:Aberration (astronomy)#Relativistic explanation|w:relativistic aberration formula]]. {{Lorentzbox|Text=Formula (2) was introduced by {{section link||Petzoldt (1914)}} and in a more general way that also allows for motions along lines ''parallel'' to the x-axis by {{section link||Lorentz (1914)|Lampa (1924)}}. Even before those authors, the visual position of a ''point'' was derived by {{section link||Mangoldt (1910)}} and related to photographic images by {{section link||Grünbaum (1911)}}.}} The visual length on a photograph ''directly'' corresponds to contraction formula (1) when the moving 1D rod is oriented ''perpendicular'' to the camera's line of sight and the rod's center is exactly in the camera's line of sight at the time of light emission, because in this case the light emanating ''simultaneously'' from both ends of the moving rod will travel the same distance to the camera and therefore arrive ''simultaneously'' as well, which can be compared to the visual length of a stationary rod that was momentarily at the same position as the moving rod when light was emanated from its endpoints. {{Lorentzbox|Text=This was demonstrated by {{section link||Lorentz (1922)}}.}} In case the rod's center is ''not'' exactly in the camera's line of sight at the time of light emission, Lorentz contraction can only be detected on photographs by resorting to approximations such as making the rod's length very small with respect to the rod's distance from the camera. {{Lorentzbox|Text=This was shown by {{section link||Mangoldt (1910)|Grünbaum (1911)|Lorentz (1914)}}.}} ;3D objects It becomes more complicated when 3D objects are considered. First we notice the conformal property of the [[w:Aberration (astronomy)#Relativistic explanation|w:relativistic aberration formula]] :(3) <math>\quad\tan\frac{\phi}{2}=\sqrt{\frac{1+v/c}{1-v/c}}\tan\frac{\phi'}{2}</math> because it only changes the scale but not the shape of spherical outlines, thus the visual appearance of spheres ''remains spherical'' on camera. {{Lorentzbox|Text=This was pointed out by {{section link||Plummer (1910)}} and rediscovered by {{section link||Penrose (1958/59) and Terrell (1959)}}.}} Furthermore, light emitted on the backside of arbitrary 3D objects such as spheres, rods and cubes can reach the camera, because the object's motion frees the path of light rays that were hidden otherwise. Consequently, if the object is very far away and subtends a very small angle, it doesn't appear contracted but rather ''rotated'' by <math>\phi-\phi'</math>. {{Lorentzbox|Text=This was pointed out by {{section link||Penrose (1958/59) and Terrell (1959)}}.}} The description of visual distortions is connected to the names of Penrose and Terrell in most papers, hence it is called [[w:Penrose–Terrell effect]]/rotation or Terrell effect/rotation or Lampa–Penrose–Terrell effect. Given the historical information provided above, the expression '''Penrose-Terrell effect''' is appropriate when it comes to rotations alone; yet when it comes to the visual appearance of moving bodies in general, one should should not forget the early contributions of Plummer, Petzoldt, Lorentz, Lampa. ==Historical papers== ===Plummer (1910)=== [[w:Henry Crozier Keating Plummer]]<ref name=plum10 /> derived the following consequence from relativistic aberration: :In the first place we may consider the stereographic projection of the celestial sphere on the tangent plane perpendicular to the direction of motion. The form of the law of aberration ::<math>\tan\frac{1}{2}\phi'=\sqrt{\frac{U-v}{U+v}}\tan\frac{1}{2}\phi</math> :shows that the effect of aberration is simply to alter the ''scale'' of the projection. But the stereographic projection is a conformal representation of the sphere. Hence actual configurations on the sphere are only changed conformally by the effect of aberration, or in other words any small area is altered only in size and not in shape. We know that aberration merely changes the scale of a photograph of a small part of the sky, and the truth of this fact now becomes independent of the velocity (however large) of the observer. Also stars which appear to lie on a circle at any one time will continue to do so permanently. {{Lorentzbox|Text=Thus Plummer showed that independent of the velocity of the observer, the ''photograph'' of parts of the celestial sphere is changed by relativistic aberration only in terms of scale, not shape, thus spherical outlines remain spherical.}} ===Mangoldt (1910)=== [[w:Hans Carl Friedrich von Mangoldt]]<ref name=mang10 /> demonstrated the constancy of light speed in different frames by using the case of a light ray emitted from the origin and then traversing distance <math>-l</math> in the negative x-direction during time <math>t=l/c</math>. A ''moving'' marker momentarily co-located at position <math>-l</math> at time <math>t</math> will indicate the Lorentz transformed value :<math>x'=\beta(x-vt)=-\beta\left(l+v\frac{l}{c}\right)=-\beta l\left(1+\frac{v}{c}\right)</math> and a momentarily co-located moving clock indicates :<math>t'=\beta\left(-\frac{v}{c^{2}}x+t\right)=\beta\left(\frac{v}{c^{2}}l+\frac{l}{c}\right)=\beta\frac{l}{c}\left(1+\frac{v}{c}\right)</math> where <math>\beta=1/\sqrt{1-v^{2}/c^{2}}</math> was used by him as Lorentz factor, proving <math>x'/t'=-c</math> as it should be. At the end of his paper, he alluded to the possibility of using ''photographs'' of ''sufficiently small areas'' at ''sufficient distance'' from the camera, which should directly provide an ''approximately'' correct image of relativistic effects such as length contraction and time dilation as indicated by markers and clocks. {{Lorentzbox|Text=a) We see that his position equation that incorporates the time-of-flight of light (using modern notation <math>\gamma</math> for the Lorentz factor) :<math>x'=-\gamma l\left(1+\frac{v}{c}\right)=l\sqrt{\frac{1+v/c}{1-v/c}}</math>, is formally equivalent to equation (2), and it's easy to re-interpret his result in terms of visual lengths: We introduce a rod whose rest length <math>l'</math> is defined by coordinate <math>x'</math> as left endpoint and the origin as right endpoint, in which case Mangoldt's distance <math>l</math> is identical with the rod's visual length <math>L</math> as photographed at time <math>t=l/c</math> by a camera located at position <math>-l</math>. b) Ironically, even though he was in possession of the optical position formula that incorporates the time-of-flight of light, he only discussed an ''approximate'' case in order to directly demonstrate length contraction and time dilation on photographic images ''without'' considering time-of-flight delays, which was clarified by {{section link||Grünbaum (1911)}}. Anyway, Mangoldt's restriction to an approximate case shows, that he was well aware that an exact treatment requires the consideration of time-of-flight delays.}} ===Grünbaum (1911)=== In a follow-up paper to {{section link||Mangoldt (1910)}}, the physicist [[w:de:Fritz Grünbaum (Physiker)|w:Fritz Grünbaum]]<ref name=gbaum /> discussed the ''photographic image'' of distant points. He described a marker (indicating its spatial position) and a co-located clock (indicating its time) that are at relative rest with respect to a photographic apparatus, and another marker/clock pair in relative motion with respect to that apparatus. When both marker/clock pairs meet each other at point P, the apparatus located at point R makes a photo of them. In the rest frame of the apparatus, <math>l</math> is the distance from P to R, and T is the time at which the image was created on the photographic plate. On that image, the resting marker indicates its spatial coordinate <math>x_{r}</math> while the resting clock indicates its time <math>t_{r}=T-l/c</math> since light took some time to traverse distance <math>l</math>. In order to find out which values are indicated on the photographic image of the ''moving'' marker/clock pair, he used the Lorentz transformation (with <math>\beta</math> as Lorentz factor): :<math>\begin{matrix}x'_{r}=\beta\left(x_{r}-vt_{r}\right)\Rightarrow\beta\left[x-v\left(T-\frac{l}{c}\right)\right]\\ t'_{r}=\beta\left(t_{r}-\frac{v}{c^{2}}x_{r}\right)\Rightarrow\beta\left[\left(T-\frac{l}{c}\right)-\frac{v}{c^{2}}x\right]\\ \left[\beta=\frac{1}{\sqrt{1-v^{2}/c^{2}}},\ x_{r}=x,\ t_{r}=T-\frac{l}{c}\right] \end{matrix}</math> which he summarized in the following table: {| cellpadding="10" |- |On the image <br />of the apparatus: |style="border-left:1px solid black" |Stationary marker: <math>x,\ y=0</math> Stationary clock: <math>T-\frac{l}{c}</math> Moving marker: <math>\beta\left[x-v\left(T-\frac{l}{c}\right)\right]</math> Moving clock: <math>\beta\left[\left(T-\frac{l}{c}\right)-\frac{v}{c^{2}}x\right]</math> |} He then described the symmetrical case when the photographic image of P is made by a ''moving'' observer B, discussed the special cases <math>T=T'=0</math> , which together with <math>x=0</math> and <math>l=y</math> and by considering time-of-flight effects, allows to indirectly recover both length contraction and time dilation as well as their symmetry by analyzing the data given on the images. Finally he clarified Mangoldt's claim according to whom one can directly demonstrate length contraction ''without'' considering time-of-flight effects: He showed that this can only be done if one strictly follows Mangoldt's requirement that the rod length <math>x</math> must be very small compared to distance <math>y</math>, which indeed produces the Lorentz contraction formula <math>x'=\beta x</math> because the differences in the emission times at the endpoints are so small that they approximately happened simultaneously. {{Lorentzbox|Text=a) His formula for the visual ''position'' of a ''photographed'' marker in motion easily allows us to derive the visual ''length'' between two points: We place R to the origin <math>x_{0}=0</math> so that point P is at position <math>x=l</math>, thus we can interpret R and P as endpoints of a horizontally aligned and moving rod measured at time <math>T=0</math>, which gives (using modern notation <math>\gamma</math> for the Lorentz factor): :<math>x'_{r}=\gamma\left[x-v\left(T-\frac{l}{c}\right)\right]\underset{{x=l\atop T=0}}{=}\gamma\left[l-\frac{v}{c}l\right]=l\sqrt{\frac{1-v/c}{1+v/c}}</math> equivalent to equation (2) by identifying his length <math>l</math> with visual length <math>L</math> and coordinate <math>x'_{r}</math> as the right endpoint of a rod of rest length <math>l'</math> whose left endpoint is at the origin. So Grünbaum correctly incorporated time-of-flight effects in order to derive the visual ''position'' of points with respect to photographs. Yet he treated the visual ''length'' of moving rods only in approximation while clarifying Mangoldt's statements. b) In a short review of Grünbaum's paper, [[w:Max von Laue]] (1911)<ref name=laue11gru /> described it as using photographic images to demonstrate Lorentz contraction. }} ===Petzoldt (1914)=== In an otherwise philosophical analysis of relativity, [[w:Joseph Petzoldt]]<ref name=petz /> demonstrated the following consequence: :The perspectivistic shape changes of bodies whose velocity is comparable to that of light, do not appear to have been investigated yet. [..] The image of an object, which is generated on the retina of the eye or on the photographic plate - as a snapshot - is produced by light coming from all the points of the object in question, but it wasn't sent at the same time: all of the light that contributes to the production of the image arrives simultaneously with the light that originated from those points of the object that were closest to the eye or plate; the further the object's point is from the plate or eye, the sooner it must send its contribution of light. The result is that the image of a receding or approaching object having a large speed comparable to that of light, does not correspond to the image of the same object if it were at rest relative to the eye or plate, but rather gives the impression that it originated from a shorter or longer object within that radius of distance. In case the object is receding from the eye or plate, the light contributed from the most distant points would have been sent later, in the case of approach it would have been sent earlier than in the state of rest. A simple calculation that takes into account the Lorentz contraction, results in the fact that the object in question whose physical length is <math>l\sqrt{1-\tfrac{v^{2}}{c^{2}}}</math>, where <math>l</math> is the length for the "co-moving" observer, would have to be assessed on the basis of this photographic momentary image as having the perspectivistic moving length: ::<math>l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c+v}\qquad</math> or <math>\qquad l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c-v}</math>, :depending on the whether the object recedes or approaches the eye or plate. {{Lorentzbox|Text=a) Petzoldt correctly derived the visual length of moving 1D rods, his results being equivalent to equation (2): :<math>\begin{matrix}l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c-v}=l\sqrt{\frac{1+v/c}{1-v/c}}\\ l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c+v}=l\sqrt{\frac{1-v/c}{1+v/c}} \end{matrix}</math> b) As explained in [[w:Joseph Petzoldt|Petzoldt's Wikipedia article]], it was [[w:Albert Einstein]] himself who publicly recommended Petzoldt's 1914 paper in a newspaper article and privately praised it by letter, which implies that by 1914, Einstein should have been aware of the pitfalls that arise when describing photographs of Lorentz contracted bodies. However, in the [[s:Relativity (1931)/Appendix 1|s:first appendix]] to his popular book [[w:Relativity: The Special and the General Theory]] that was added to the third edition from 1918 and still remains in modern editions,<ref name=einst17pop /> he seems to have overlooked this fact. Einstein argued that <math>\Delta x=1/a</math> is the length indicated on a "snapshot" or "instantaneous photograph" of a unit length at rest in K' that was taken from system K at time <math>t=0</math>, and that <math>\Delta x'=a\left(1-v^{2}/c^{2}\right)</math> is the length indicated on a snapshot of a unit length at rest in K that was taken from system K' at time <math>t'=0</math>; since symmetry requires that <math>\Delta x=\Delta x'</math>, he concluded that <math>a^{2}=1/\left(1-v^{2}/c^{2}\right)</math>. If we plug his result into his snapshot length equations we get <math>\Delta x=\sqrt{1-v^{2}/c^{2}}</math> and symmetrically <math>\Delta x'=\sqrt{1-v^{2}/c^{2}}</math>, identical to the Lorentz contraction of unit rest lengths. Yet while Einstein's derivation is correct, his choice of visualizing this result in terms of "snapshots" can be misleading since one has to consider time-of-flight effects which leads to visual deviations in most cases. }} ===Lorentz (1914)=== [[File:Lorentz1914-2.png|250px|right]] [[w:Hendrik Lorentz]] (March 1914)<ref name=lorentz14 /> described two rulers along line EF, one at rest with respect to observer A having length <math>l'=l</math> and the other moving with respect to A with velocity <math>v</math> having contracted length <math>l'=l/a</math> (where <math>a</math> is the Lorentz factor). He then derived a general formula for the approximated visual length <math>s</math> of the rods as a function of <math>l'</math>, using an photographic apparatus moving with velocity <math>w</math>. On the screen of the apparatus there is a small slot D situated at vertical distance L from E, and below there is a photographic plate at vertical distance <math>\lambda</math> from D. Then slot D is opened for one moment, during which it is passed by optical signals from endpoints F and G of the rods (where <math>FG=l'</math>), reaching points f and g on the plate. Since the signals reaching D at the same time are sent from different locations, they were not emitted simultaneously. Assuming the signal from F was sent at time <math>t_{0}</math> at position <math>x_{0}</math> after which it traverses distance <math>\sqrt{L^{2}+x_{0}^{2}}</math> to D, it follows that the signal from G was sent at an earlier time <math>t_{0}+\tau</math> at position <math>x_{1}=x_{0}+l'+v\tau</math> after which it traverses distance <math>\sqrt{L^{2}+\left(x_{0}+l'+v\tau\right)^{2}}</math> to D. Thus the value of <math>\tau</math> is given by :<math>\sqrt{L^{2}+\left(x_{0}+l'+v\tau\right)^{2}}-\sqrt{L^{2}+x_{0}^{2}}=-c\tau</math> or using angle <math>EDF=\phi_{0}</math> and assuming very large L by which terms containing <math>l'^{2}</math> and <math>\tau^{2}</math> can be neglected: :<math>\tau=-\frac{\sin\phi_{0}}{c+v\sin\phi_{0}}l'</math>, thus <math>x_{1}=x_{0}+\frac{cl'}{c+v\sin\phi_{0}}</math>. After deriving the position of points f and g on the plate, and under consideration that the plate was moving with velocity <math>w</math>, he obtained the general formula representing the approximated visual length of rods: :<math>s=\frac{\lambda}{L}\frac{c+w\sin\phi_{0}}{c+v\sin\phi_{0}}l'</math>. The visual length <math>s_{1}</math> of the resting rod follows by plugging in <math>v=0</math> and <math>l'=l</math>, whereas visual length <math>s_{2}</math> of the moving rod follows by plugging in <math>l'=l/a</math> (where <math>a</math> is the Lorentz factor), thus :<math>\frac{s_{1}}{s_{2}}=\left(1+\frac{v}{c}\sin\phi_{0}\right)a</math>. He showed that the case <math>\phi_{0}=0</math> allows to recover the Lorentz contraction formula :<math>\frac{s_{1}}{s_{2}}=a</math>, which is possible because in this approximation neglecting terms containing <math>l'^{2}</math>, one can pretend as if the emission of the light signals at F and G happened simultaneously. {{Lorentzbox|Text=a) Setting <math>\phi_{0}=\pi/2</math> in the case of 90 degrees, his formula produces (with <math>a</math> as Lorentz factor): :<math>\frac{s_{1}}{s_{2}}=\left(1+\frac{v}{c}\right)a=\sqrt{\frac{1+v/c}{1-v/c}}</math> equivalent to the longitudinal visual length formula (2), independently derived by {{section link||Petzoldt (1914)}}. b) Lorentz's last case <math>\phi_{0}=0</math> agrees with {{section link||Mangoldt (1910)|Grünbaum (1911)}} who argued that Lorentz contraction can be recovered from the data on photographs under certain approximations.}} ===Lorentz (1922)=== In 1922 (published 1927),<ref name=lorentz22 /> [[w:Hendrik Lorentz]] simplified his earlier treatment of 1914 by writing: [[File:Lorentz1927-31.png|250px|right]] :Let there be two “equal” rods P and Q, placed along the line AB parallel to OZ, and let the first be at rest in x, y, z, t, the other in x’, y’, z’, t’. The screen CD coincides with the plane YOZ, the distance OK being <math>p</math>, and EF is the photographic plate, at a distance <math>OM=q</math> behind the screen. :In A’s experiment the screen and the photographic plate are at rest in the system x, y, z, the pinhole being constantly at the origin O of those coordinates. We shall suppose it to be opened for an instant at time <math>t=0</math>, and we shall define the “effective” position of a moving point by the condition that light emitted by the point in that position shall reach the hole O just when it is opened; the time at which the effective position is reached may be called the effective time. We shall denote by <math>2l</math> the length of the rod P in the system x, y, z, so that in the same system <math>2a/l</math> [with <math>a</math> as Lorentz factor] is the length of Q. For the sake of simplicity we shall suppose <math>l</math> to be so small that terms with <math>l^{2}</math> may be neglected. :Now A must be sure that he compares ''simultaneous'' positions of the ends of the moving rod Q. He can satisfy this condition by arranging the experiment in such a way that the middle point of Q passes through <math>K(z=0)</math> at the time <math>-p/c</math>. We shall further assume that the middle point of P always has this position. :It is easily seen that in this first experiment the images of the two rods have the lengths <math>2\tfrac{q}{p}l</math> and <math>2\tfrac{q}{p}\tfrac{l}{a}</math>, the second being <math>a</math> times shorter than the first. {{Lorentzbox|Text=a) Lorentz's method, in which both endpoints of the rod have the same distance to hole O, can indeed accurately represent the different lengths of resting and moving 1D rods on a photograph. b) As later shown by {{section link||Penrose (1958/59) and Terrell (1959)}}, this method doesn't work anymore when 3D objects are considered.}} ===Lampa (1924)=== [[w:de:Anton Lampa]]<ref name=Lampa /> devoted an entire paper to the question of the visual length of moving rods. He pointed out, that the relativistic length contraction formula doesn't say anything about the visual appearance of moving rods from the perspective of non-comoving observers. He started by defining a rod of rest length <math>l'</math> with endpoint coordinates <math>x'_{A}=y'_{A}=0</math> and <math>x'_{B}=l',\,y'_{B}=0</math>, letting a light signal be sent from B to the origin starting at time <math>t'_{B}=-l'/c</math> and arriving at time <math>t'=0</math>. The Lorentz transformation into another frame K which is ''moving'' parallel to the x-axis gives: :<math>\begin{align}x_{B} & =\frac{x'_{B}+vt'_{B}}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=\frac{l'-\frac{v}{c}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=l'\frac{\sqrt{1-\frac{v^{2}}{c^{2}}}}{1+\frac{v}{c}}\\ t_{B} & =\frac{t'_{B}+\frac{v}{c^{2}}x'_{B}}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=\frac{-\frac{l'}{c}+\frac{v}{c^{2}}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=-\frac{l'}{c}\frac{\sqrt{1-\frac{v^{2}}{c^{2}}}}{1+\frac{v}{c}} \end{align} </math> from which he derived the Lorentz contracted length as follows: :<math>l=x_{B}+v(0-t_{B})=x_{B}-vt_{B}=l'\sqrt{1-v^{2}/c^{2}}</math> {{Lorentzbox|Text=As in the case of {{section link||Mangoldt (1910)}}, Lampa's position formula that incorporates the time-of-flight of light :<math>x_{B}=l'\frac{\sqrt{1-v^{2}/c^{2}}}{1+v/c}=l'\sqrt{\frac{1-v/c}{1+v/c}}</math>, is equivalent to equation (2) by re-interpreting <math>x_{A}=0</math> and <math>x_{B}</math> as endpoints defining the visual length of the rod.}} In order to explicitly derive the visual length of the rod, he discussed a more general case in which the endpoints A and B of the rod at rest in frame K' are given by coordinates <math>x'_{A}=0,\,y'_{A}=y'</math> and <math>x'_{B}=l',\,y'_{B}=y'</math>. So when an observer resting at the origin sees the rod at time <math>t'=0</math> , the rod's light must have been sent earlier at time <math>t'_{A}=-y'/c</math> from A and at an even earlier time <math>t'_{B}=-\sqrt{y^{\prime2}+l^{\prime2}}/c</math> from B. Applying the Lorentz transformation, he showed that the visual distance <math>\lambda</math> between A and B seen by an observer at the origin of another frame K which is ''moving'' parallel to the x-axis, is given as follows: :<math>\lambda=x_{B}-x_{A}=\frac{l'-\frac{v}{c}\left(\sqrt{y^{\prime2}+l^{\prime2}}-y'\right)}{\sqrt{1-\frac{v^{2}}{c^{2}}}}</math> He concluded: :This distance is a function of <math>v/c</math> at given <math>l'</math> and <math>y'</math>. If <math>v=0</math> or <math>v/c=0</math>, we have <math>x_{B}=l'</math> and <math>x_{A}=0</math>, thus <math>\lambda=l'</math> as it must be, because the coordinate systems always coincide at <math>v=0</math>. If we increase <math>v/c</math> beginning with value zero, then <math>x_{B}</math> decreases and finally becomes negative, while the absolute value of <math>x_{A}</math> steadily increases; <math>x_{B}-x_{A}</math> initially decreases, then reaches a minimum and then permanently increases. If <math>v/c=l'/\sqrt{y^{\prime2}+l^{\prime2}}</math>, then <math>x_{B}=0</math> and <math>x_{A}=-l'</math> and <math>\lambda</math> becomes equal to <math>l'</math>. We see that the distance of the points from which the light rays emanate as measured in system K of the stationary observer, is not at all smaller than the length of the rod measured in the coordinate system attached to it; it even becomes infinitely large if the rod moves relative to the observer with the speed of light. Yet the visual angle under which the stationary observer sees points A and B of the rod, is always finite. In frame K, he defined <math>\alpha</math> as angle of the light ray emanating from endpoint A at time <math>t_{A}</math> and <math>\beta</math> as angle of the light ray emanating from endpoint B at time <math>t_{B}</math>, and then derived the relation between the [[w:visual angle]] <math>\varphi=\beta-\alpha</math> observed in K and angle <math>\varphi'</math> observed in K' by: :<math>\begin{matrix}\sin\varphi=\sin(\beta-\alpha)=\sin\beta\cos\alpha-\cos\beta\sin\alpha\\ \sin\varphi'=\frac{l'}{\sqrt{y^{\prime2}+l^{\prime2}}},\ \cos\varphi'=\frac{y'}{\sqrt{y^{\prime2}+l^{\prime2}}}\\ \Downarrow\\ \sin\varphi=\frac{\sin\varphi'-\frac{v}{c}(1-\cos\varphi')}{1-\frac{v}{c}\sin\varphi'}\sqrt{1-\frac{v^{2}}{c^{2}}} \end{matrix}</math> He finally showed how to recover the Lorentz contracted length <math>l</math> from visual length <math>\lambda</math>: :<math>\begin{align}l & =\lambda+v\left(t_{A}-t_{B}\right)\\ & =l'\sqrt{1-\frac{v^{2}}{c^{2}}} \end{align} </math> which he rewrote in terms of angles <math>\alpha</math> and <math>\beta</math> as: :<math>\begin{align}\lambda & =y'(\tan\beta-\tan\alpha);\quad t_{A}-t_{B}=\frac{y'}{c}\left(\frac{1}{\cos\beta}-\frac{1}{\cos\alpha}\right)\\ \Rightarrow l & =y'\left[(\tan\beta-\tan\alpha)+\frac{v}{c}\left(\frac{1}{\cos\beta}-\frac{1}{\cos\alpha}\right)\right] \end{align} </math> {{Lorentzbox|Text=a) Lampa's formula for <math>\lambda</math> is more general than equation (2), producing the latter in the special case <math>y'=0</math>: :<math>\lambda=\frac{l'-\frac{v}{c}\left(\sqrt{y^{\prime2}+l^{\prime2}}-y'\right)}{\sqrt{1-\frac{v^{2}}{c^{2}}}}\underset{y'=0}{=}\frac{l'-\frac{v}{c}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=l'\sqrt{\frac{1-v/c}{1+v/c}}</math> b) He was evidently unaware of previous work on visual positions and lengths by {{section link||Grünbaum (1911)|Petzoldt (1914)|Lorentz (1914)}}. c) In a short review of Lampa's paper, [[w:Cornelius Lanczos]] (1925)<ref name=lanc25 /> described it as deriving the relation between the visual angles of a moving rod seen by resting and moving observers, as well as deriving the length of the rod from the data of its appearance.}} ===Penrose (1958/59) and Terrell (1959)=== {{section link||Petzoldt (1914)|Lorentz (1914)|Lampa (1924)}} restricted their investigations to the visual appearance of 1D rods, whereas the only early description of the visual appearance of 3D objects was given by {{section link||Plummer (1910)}} in relation to the celestial sphere based on the conformal property of aberration. However, these early investigations were evidently completely forgotten, and it took decades before those questions were taken up again: Using the conformal property of aberration, [[w:Roger Penrose]] (1958/59)<ref name=Penrose /> described the visual appearance of spheres, and discovered a completely new effect: Due to the motion of the sphere, points that were in the background become visible due to the sphere's motion, leading to the effect that the sphere appears not to be Lorentz contracted but rather rotated. Independently, [[w:James Terrell]] (1959)<ref name=Terrell /> noticed the same rotation effect in relation to 3D rods, leading him to famously declare the "invisibility of the Lorentz contraction". Independently, the special case of the visual length of 1D rods was discussed by Weinstein (1959/60).<ref name=wein60 /> A large number of follow-up papers by many authors appeared, which demonstrate the visual appearance of 1D and 3D objects in detail, see [[w:Penrose-Terrell effect]]. ==References== ===Historical references=== <references> <ref name=plum10>{{replace|{{#section:History of Topics in Special Relativity/relsource|plum10}}|*||count=1}}</ref> <ref name=mang10>{{replace|{{#section:History of Topics in Special Relativity/relsource|mang10}}|*||count=1}}</ref> <ref name=gbaum>{{replace|{{#section:History of Topics in Special Relativity/relsource|gbaum}}|*||count=1}}</ref> <ref name=laue11gru>{{replace|{{#section:History of Topics in Special Relativity/relsource|laue11gru}}|*||count=1}}</ref> <ref name=petz>{{replace|{{#section:History of Topics in Special Relativity/relsource|petz}}|*||count=1}}</ref> <ref name=einst17pop>{{replace|{{#section:History of Topics in Special Relativity/relsource|einst17pop}}|*||count=1}}</ref> <ref name=Lampa>{{replace|{{#section:History of Topics in Special Relativity/relsource|Lampa}}|*||count=1}}</ref> <ref name=lanc25>{{replace|{{#section:History of Topics in Special Relativity/relsource|lanc25}}|*||count=1}}</ref> <ref name=Penrose>{{replace|{{#section:History of Topics in Special Relativity/relsource|Penrose}}|*||count=1}}</ref> <ref name=Terrell>{{replace|{{#section:History of Topics in Special Relativity/relsource|Terrell}}|*||count=1}}</ref> <ref name=wein60>{{replace|{{#section:History of Topics in Special Relativity/relsource|wein60}}|*||count=1}}</ref> <ref name=lorentz14>{{replace|{{#section:History of Topics in Special Relativity/relsource|lorentz14}}|*||count=1}}</ref> <ref name=lorentz22>{{replace|{{#section:History of Topics in Special Relativity/relsource|lorentz22}}|*||count=1}}</ref> </references> ===Further reading=== <references group=S /> [[Category:History of special relativity]] h5oo1mgg6zrhrghlc6cal697wls56kv 2835369 2835368 2026-10-01T17:14:50Z D.H 52339 /* Lampa (1924) */ 2835369 wikitext text/x-wiki {| style="width:20%; font-size:13px;" align=right |{{../Other Topics (header)}} |} ==Early history of the Penrose–Terrell effect== {{Lorentzbox|Text={{center|Date of article creation: 19 July 2025; Last major revision: 12 December 2025}}}} If the length of an object is measured exactly at the locations of its endpoints, then its [[w:rest length]] <math>l'</math> is related to its length <math>l</math> in a relatively moving frame by the [[w:length contraction]] formula: :(1) <math>\quad l=l'\sqrt{1-v^{2}/c^{2}}</math> However, it turns out that the ''visual appearance'' of that object when photographed from a distance leads to quite different results, because optical aberration and time-of-flight effects have to be considered as well. In particular, light rays arriving simultaneously at the camera weren't emitted simultaneously from all locations at the source.<ref group=S name=space>A very detailed account of the visual appearance of moving bodies is presented on the website [https://www.spacetimetravel.org/ Space Time Travel] which is based on the German website [https://www.tempolimit-lichtgeschwindigkeit.de/ Tempolimit Lichtgeschwindigkeit], where the accompanied paper [https://www.tempolimit-lichtgeschwindigkeit.de/phantom/pdnw97.pdf Appearance of relativistically moving objects (in German)] gives the formula for the length of 1D rods, followed by descriptions of rotated cubes and spheres.</ref> ;1D rods The visual length <math>L</math> of a 1D rod that is both oriented and moving ''along'' the x-axis, and which approaches or recedes a camera that is located on the same x-axis, is given by :(2) <math>\quad\begin{matrix}L_{{\rm approach}}=\frac{l}{1-v/c}=l'\sqrt{\frac{1+v/c}{1-v/c}}\\ L_{{\rm recede}}=\frac{l}{1+v/c}=l'\sqrt{\frac{1-v/c}{1+v/c}} \end{matrix}</math> So if the 1D rod approaches it appears to be longer, if it recedes it appears to be shorter, and none of those lengths precisely matches the contraction formula (1) but rather depend on the [[w:Relativistic_Doppler_effect|w:relativistic Doppler factor]] that also appears in the [[w:Aberration (astronomy)#Relativistic explanation|w:relativistic aberration formula]]. {{Lorentzbox|Text=Formula (2) was introduced by {{section link||Petzoldt (1914)}} and in a more general way that also allows for motions along lines ''parallel'' to the x-axis by {{section link||Lorentz (1914)|Lampa (1924)}}. Even before those authors, the visual position of a ''point'' was derived by {{section link||Mangoldt (1910)}} and related to photographic images by {{section link||Grünbaum (1911)}}.}} The visual length on a photograph ''directly'' corresponds to contraction formula (1) when the moving 1D rod is oriented ''perpendicular'' to the camera's line of sight and the rod's center is exactly in the camera's line of sight at the time of light emission, because in this case the light emanating ''simultaneously'' from both ends of the moving rod will travel the same distance to the camera and therefore arrive ''simultaneously'' as well, which can be compared to the visual length of a stationary rod that was momentarily at the same position as the moving rod when light was emanated from its endpoints. {{Lorentzbox|Text=This was demonstrated by {{section link||Lorentz (1922)}}.}} In case the rod's center is ''not'' exactly in the camera's line of sight at the time of light emission, Lorentz contraction can only be detected on photographs by resorting to approximations such as making the rod's length very small with respect to the rod's distance from the camera. {{Lorentzbox|Text=This was shown by {{section link||Mangoldt (1910)|Grünbaum (1911)|Lorentz (1914)}}.}} ;3D objects It becomes more complicated when 3D objects are considered. First we notice the conformal property of the [[w:Aberration (astronomy)#Relativistic explanation|w:relativistic aberration formula]] :(3) <math>\quad\tan\frac{\phi}{2}=\sqrt{\frac{1+v/c}{1-v/c}}\tan\frac{\phi'}{2}</math> because it only changes the scale but not the shape of spherical outlines, thus the visual appearance of spheres ''remains spherical'' on camera. {{Lorentzbox|Text=This was pointed out by {{section link||Plummer (1910)}} and rediscovered by {{section link||Penrose (1958/59) and Terrell (1959)}}.}} Furthermore, light emitted on the backside of arbitrary 3D objects such as spheres, rods and cubes can reach the camera, because the object's motion frees the path of light rays that were hidden otherwise. Consequently, if the object is very far away and subtends a very small angle, it doesn't appear contracted but rather ''rotated'' by <math>\phi-\phi'</math>. {{Lorentzbox|Text=This was pointed out by {{section link||Penrose (1958/59) and Terrell (1959)}}.}} The description of visual distortions is connected to the names of Penrose and Terrell in most papers, hence it is called [[w:Penrose–Terrell effect]]/rotation or Terrell effect/rotation or Lampa–Penrose–Terrell effect. Given the historical information provided above, the expression '''Penrose-Terrell effect''' is appropriate when it comes to rotations alone; yet when it comes to the visual appearance of moving bodies in general, one should should not forget the early contributions of Plummer, Petzoldt, Lorentz, Lampa. ==Historical papers== ===Plummer (1910)=== [[w:Henry Crozier Keating Plummer]]<ref name=plum10 /> derived the following consequence from relativistic aberration: :In the first place we may consider the stereographic projection of the celestial sphere on the tangent plane perpendicular to the direction of motion. The form of the law of aberration ::<math>\tan\frac{1}{2}\phi'=\sqrt{\frac{U-v}{U+v}}\tan\frac{1}{2}\phi</math> :shows that the effect of aberration is simply to alter the ''scale'' of the projection. But the stereographic projection is a conformal representation of the sphere. Hence actual configurations on the sphere are only changed conformally by the effect of aberration, or in other words any small area is altered only in size and not in shape. We know that aberration merely changes the scale of a photograph of a small part of the sky, and the truth of this fact now becomes independent of the velocity (however large) of the observer. Also stars which appear to lie on a circle at any one time will continue to do so permanently. {{Lorentzbox|Text=Thus Plummer showed that independent of the velocity of the observer, the ''photograph'' of parts of the celestial sphere is changed by relativistic aberration only in terms of scale, not shape, thus spherical outlines remain spherical.}} ===Mangoldt (1910)=== [[w:Hans Carl Friedrich von Mangoldt]]<ref name=mang10 /> demonstrated the constancy of light speed in different frames by using the case of a light ray emitted from the origin and then traversing distance <math>-l</math> in the negative x-direction during time <math>t=l/c</math>. A ''moving'' marker momentarily co-located at position <math>-l</math> at time <math>t</math> will indicate the Lorentz transformed value :<math>x'=\beta(x-vt)=-\beta\left(l+v\frac{l}{c}\right)=-\beta l\left(1+\frac{v}{c}\right)</math> and a momentarily co-located moving clock indicates :<math>t'=\beta\left(-\frac{v}{c^{2}}x+t\right)=\beta\left(\frac{v}{c^{2}}l+\frac{l}{c}\right)=\beta\frac{l}{c}\left(1+\frac{v}{c}\right)</math> where <math>\beta=1/\sqrt{1-v^{2}/c^{2}}</math> was used by him as Lorentz factor, proving <math>x'/t'=-c</math> as it should be. At the end of his paper, he alluded to the possibility of using ''photographs'' of ''sufficiently small areas'' at ''sufficient distance'' from the camera, which should directly provide an ''approximately'' correct image of relativistic effects such as length contraction and time dilation as indicated by markers and clocks. {{Lorentzbox|Text=a) We see that his position equation that incorporates the time-of-flight of light (using modern notation <math>\gamma</math> for the Lorentz factor) :<math>x'=-\gamma l\left(1+\frac{v}{c}\right)=l\sqrt{\frac{1+v/c}{1-v/c}}</math>, is formally equivalent to equation (2), and it's easy to re-interpret his result in terms of visual lengths: We introduce a rod whose rest length <math>l'</math> is defined by coordinate <math>x'</math> as left endpoint and the origin as right endpoint, in which case Mangoldt's distance <math>l</math> is identical with the rod's visual length <math>L</math> as photographed at time <math>t=l/c</math> by a camera located at position <math>-l</math>. b) Ironically, even though he was in possession of the optical position formula that incorporates the time-of-flight of light, he only discussed an ''approximate'' case in order to directly demonstrate length contraction and time dilation on photographic images ''without'' considering time-of-flight delays, which was clarified by {{section link||Grünbaum (1911)}}. Anyway, Mangoldt's restriction to an approximate case shows, that he was well aware that an exact treatment requires the consideration of time-of-flight delays.}} ===Grünbaum (1911)=== In a follow-up paper to {{section link||Mangoldt (1910)}}, the physicist [[w:de:Fritz Grünbaum (Physiker)|w:Fritz Grünbaum]]<ref name=gbaum /> discussed the ''photographic image'' of distant points. He described a marker (indicating its spatial position) and a co-located clock (indicating its time) that are at relative rest with respect to a photographic apparatus, and another marker/clock pair in relative motion with respect to that apparatus. When both marker/clock pairs meet each other at point P, the apparatus located at point R makes a photo of them. In the rest frame of the apparatus, <math>l</math> is the distance from P to R, and T is the time at which the image was created on the photographic plate. On that image, the resting marker indicates its spatial coordinate <math>x_{r}</math> while the resting clock indicates its time <math>t_{r}=T-l/c</math> since light took some time to traverse distance <math>l</math>. In order to find out which values are indicated on the photographic image of the ''moving'' marker/clock pair, he used the Lorentz transformation (with <math>\beta</math> as Lorentz factor): :<math>\begin{matrix}x'_{r}=\beta\left(x_{r}-vt_{r}\right)\Rightarrow\beta\left[x-v\left(T-\frac{l}{c}\right)\right]\\ t'_{r}=\beta\left(t_{r}-\frac{v}{c^{2}}x_{r}\right)\Rightarrow\beta\left[\left(T-\frac{l}{c}\right)-\frac{v}{c^{2}}x\right]\\ \left[\beta=\frac{1}{\sqrt{1-v^{2}/c^{2}}},\ x_{r}=x,\ t_{r}=T-\frac{l}{c}\right] \end{matrix}</math> which he summarized in the following table: {| cellpadding="10" |- |On the image <br />of the apparatus: |style="border-left:1px solid black" |Stationary marker: <math>x,\ y=0</math> Stationary clock: <math>T-\frac{l}{c}</math> Moving marker: <math>\beta\left[x-v\left(T-\frac{l}{c}\right)\right]</math> Moving clock: <math>\beta\left[\left(T-\frac{l}{c}\right)-\frac{v}{c^{2}}x\right]</math> |} He then described the symmetrical case when the photographic image of P is made by a ''moving'' observer B, discussed the special cases <math>T=T'=0</math> , which together with <math>x=0</math> and <math>l=y</math> and by considering time-of-flight effects, allows to indirectly recover both length contraction and time dilation as well as their symmetry by analyzing the data given on the images. Finally he clarified Mangoldt's claim according to whom one can directly demonstrate length contraction ''without'' considering time-of-flight effects: He showed that this can only be done if one strictly follows Mangoldt's requirement that the rod length <math>x</math> must be very small compared to distance <math>y</math>, which indeed produces the Lorentz contraction formula <math>x'=\beta x</math> because the differences in the emission times at the endpoints are so small that they approximately happened simultaneously. {{Lorentzbox|Text=a) His formula for the visual ''position'' of a ''photographed'' marker in motion easily allows us to derive the visual ''length'' between two points: We place R to the origin <math>x_{0}=0</math> so that point P is at position <math>x=l</math>, thus we can interpret R and P as endpoints of a horizontally aligned and moving rod measured at time <math>T=0</math>, which gives (using modern notation <math>\gamma</math> for the Lorentz factor): :<math>x'_{r}=\gamma\left[x-v\left(T-\frac{l}{c}\right)\right]\underset{{x=l\atop T=0}}{=}\gamma\left[l-\frac{v}{c}l\right]=l\sqrt{\frac{1-v/c}{1+v/c}}</math> equivalent to equation (2) by identifying his length <math>l</math> with visual length <math>L</math> and coordinate <math>x'_{r}</math> as the right endpoint of a rod of rest length <math>l'</math> whose left endpoint is at the origin. So Grünbaum correctly incorporated time-of-flight effects in order to derive the visual ''position'' of points with respect to photographs. Yet he treated the visual ''length'' of moving rods only in approximation while clarifying Mangoldt's statements. b) In a short review of Grünbaum's paper, [[w:Max von Laue]] (1911)<ref name=laue11gru /> described it as using photographic images to demonstrate Lorentz contraction. }} ===Petzoldt (1914)=== In an otherwise philosophical analysis of relativity, [[w:Joseph Petzoldt]]<ref name=petz /> demonstrated the following consequence: :The perspectivistic shape changes of bodies whose velocity is comparable to that of light, do not appear to have been investigated yet. [..] The image of an object, which is generated on the retina of the eye or on the photographic plate - as a snapshot - is produced by light coming from all the points of the object in question, but it wasn't sent at the same time: all of the light that contributes to the production of the image arrives simultaneously with the light that originated from those points of the object that were closest to the eye or plate; the further the object's point is from the plate or eye, the sooner it must send its contribution of light. The result is that the image of a receding or approaching object having a large speed comparable to that of light, does not correspond to the image of the same object if it were at rest relative to the eye or plate, but rather gives the impression that it originated from a shorter or longer object within that radius of distance. In case the object is receding from the eye or plate, the light contributed from the most distant points would have been sent later, in the case of approach it would have been sent earlier than in the state of rest. A simple calculation that takes into account the Lorentz contraction, results in the fact that the object in question whose physical length is <math>l\sqrt{1-\tfrac{v^{2}}{c^{2}}}</math>, where <math>l</math> is the length for the "co-moving" observer, would have to be assessed on the basis of this photographic momentary image as having the perspectivistic moving length: ::<math>l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c+v}\qquad</math> or <math>\qquad l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c-v}</math>, :depending on the whether the object recedes or approaches the eye or plate. {{Lorentzbox|Text=a) Petzoldt correctly derived the visual length of moving 1D rods, his results being equivalent to equation (2): :<math>\begin{matrix}l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c-v}=l\sqrt{\frac{1+v/c}{1-v/c}}\\ l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c+v}=l\sqrt{\frac{1-v/c}{1+v/c}} \end{matrix}</math> b) As explained in [[w:Joseph Petzoldt|Petzoldt's Wikipedia article]], it was [[w:Albert Einstein]] himself who publicly recommended Petzoldt's 1914 paper in a newspaper article and privately praised it by letter, which implies that by 1914, Einstein should have been aware of the pitfalls that arise when describing photographs of Lorentz contracted bodies. However, in the [[s:Relativity (1931)/Appendix 1|s:first appendix]] to his popular book [[w:Relativity: The Special and the General Theory]] that was added to the third edition from 1918 and still remains in modern editions,<ref name=einst17pop /> he seems to have overlooked this fact. Einstein argued that <math>\Delta x=1/a</math> is the length indicated on a "snapshot" or "instantaneous photograph" of a unit length at rest in K' that was taken from system K at time <math>t=0</math>, and that <math>\Delta x'=a\left(1-v^{2}/c^{2}\right)</math> is the length indicated on a snapshot of a unit length at rest in K that was taken from system K' at time <math>t'=0</math>; since symmetry requires that <math>\Delta x=\Delta x'</math>, he concluded that <math>a^{2}=1/\left(1-v^{2}/c^{2}\right)</math>. If we plug his result into his snapshot length equations we get <math>\Delta x=\sqrt{1-v^{2}/c^{2}}</math> and symmetrically <math>\Delta x'=\sqrt{1-v^{2}/c^{2}}</math>, identical to the Lorentz contraction of unit rest lengths. Yet while Einstein's derivation is correct, his choice of visualizing this result in terms of "snapshots" can be misleading since one has to consider time-of-flight effects which leads to visual deviations in most cases. }} ===Lorentz (1914)=== [[File:Lorentz1914-2.png|250px|right]] [[w:Hendrik Lorentz]] (March 1914)<ref name=lorentz14 /> described two rulers along line EF, one at rest with respect to observer A having length <math>l'=l</math> and the other moving with respect to A with velocity <math>v</math> having contracted length <math>l'=l/a</math> (where <math>a</math> is the Lorentz factor). He then derived a general formula for the approximated visual length <math>s</math> of the rods as a function of <math>l'</math>, using an photographic apparatus moving with velocity <math>w</math>. On the screen of the apparatus there is a small slot D situated at vertical distance L from E, and below there is a photographic plate at vertical distance <math>\lambda</math> from D. Then slot D is opened for one moment, during which it is passed by optical signals from endpoints F and G of the rods (where <math>FG=l'</math>), reaching points f and g on the plate. Since the signals reaching D at the same time are sent from different locations, they were not emitted simultaneously. Assuming the signal from F was sent at time <math>t_{0}</math> at position <math>x_{0}</math> after which it traverses distance <math>\sqrt{L^{2}+x_{0}^{2}}</math> to D, it follows that the signal from G was sent at an earlier time <math>t_{0}+\tau</math> at position <math>x_{1}=x_{0}+l'+v\tau</math> after which it traverses distance <math>\sqrt{L^{2}+\left(x_{0}+l'+v\tau\right)^{2}}</math> to D. Thus the value of <math>\tau</math> is given by :<math>\sqrt{L^{2}+\left(x_{0}+l'+v\tau\right)^{2}}-\sqrt{L^{2}+x_{0}^{2}}=-c\tau</math> or using angle <math>EDF=\phi_{0}</math> and assuming very large L by which terms containing <math>l'^{2}</math> and <math>\tau^{2}</math> can be neglected: :<math>\tau=-\frac{\sin\phi_{0}}{c+v\sin\phi_{0}}l'</math>, thus <math>x_{1}=x_{0}+\frac{cl'}{c+v\sin\phi_{0}}</math>. After deriving the position of points f and g on the plate, and under consideration that the plate was moving with velocity <math>w</math>, he obtained the general formula representing the approximated visual length of rods: :<math>s=\frac{\lambda}{L}\frac{c+w\sin\phi_{0}}{c+v\sin\phi_{0}}l'</math>. The visual length <math>s_{1}</math> of the resting rod follows by plugging in <math>v=0</math> and <math>l'=l</math>, whereas visual length <math>s_{2}</math> of the moving rod follows by plugging in <math>l'=l/a</math> (where <math>a</math> is the Lorentz factor), thus :<math>\frac{s_{1}}{s_{2}}=\left(1+\frac{v}{c}\sin\phi_{0}\right)a</math>. He showed that the case <math>\phi_{0}=0</math> allows to recover the Lorentz contraction formula :<math>\frac{s_{1}}{s_{2}}=a</math>, which is possible because in this approximation neglecting terms containing <math>l'^{2}</math>, one can pretend as if the emission of the light signals at F and G happened simultaneously. {{Lorentzbox|Text=a) Setting <math>\phi_{0}=\pi/2</math> in the case of 90 degrees, his formula produces (with <math>a</math> as Lorentz factor): :<math>\frac{s_{1}}{s_{2}}=\left(1+\frac{v}{c}\right)a=\sqrt{\frac{1+v/c}{1-v/c}}</math> equivalent to the longitudinal visual length formula (2), independently derived by {{section link||Petzoldt (1914)}}. b) Lorentz's last case <math>\phi_{0}=0</math> agrees with {{section link||Mangoldt (1910)|Grünbaum (1911)}} who argued that Lorentz contraction can be recovered from the data on photographs under certain approximations.}} ===Lorentz (1922)=== In 1922 (published 1927),<ref name=lorentz22 /> [[w:Hendrik Lorentz]] simplified his earlier treatment of 1914 by writing: [[File:Lorentz1927-31.png|250px|right]] :Let there be two “equal” rods P and Q, placed along the line AB parallel to OZ, and let the first be at rest in x, y, z, t, the other in x’, y’, z’, t’. The screen CD coincides with the plane YOZ, the distance OK being <math>p</math>, and EF is the photographic plate, at a distance <math>OM=q</math> behind the screen. :In A’s experiment the screen and the photographic plate are at rest in the system x, y, z, the pinhole being constantly at the origin O of those coordinates. We shall suppose it to be opened for an instant at time <math>t=0</math>, and we shall define the “effective” position of a moving point by the condition that light emitted by the point in that position shall reach the hole O just when it is opened; the time at which the effective position is reached may be called the effective time. We shall denote by <math>2l</math> the length of the rod P in the system x, y, z, so that in the same system <math>2a/l</math> [with <math>a</math> as Lorentz factor] is the length of Q. For the sake of simplicity we shall suppose <math>l</math> to be so small that terms with <math>l^{2}</math> may be neglected. :Now A must be sure that he compares ''simultaneous'' positions of the ends of the moving rod Q. He can satisfy this condition by arranging the experiment in such a way that the middle point of Q passes through <math>K(z=0)</math> at the time <math>-p/c</math>. We shall further assume that the middle point of P always has this position. :It is easily seen that in this first experiment the images of the two rods have the lengths <math>2\tfrac{q}{p}l</math> and <math>2\tfrac{q}{p}\tfrac{l}{a}</math>, the second being <math>a</math> times shorter than the first. {{Lorentzbox|Text=a) Lorentz's method, in which both endpoints of the rod have the same distance to hole O, can indeed accurately represent the different lengths of resting and moving 1D rods on a photograph. b) As later shown by {{section link||Penrose (1958/59) and Terrell (1959)}}, this method doesn't work anymore when 3D objects are considered.}} ===Lampa (1924)=== [[w:Anton Lampa]]<ref name=Lampa /> devoted an entire paper to the question of the visual length of moving rods. He pointed out, that the relativistic length contraction formula doesn't say anything about the visual appearance of moving rods from the perspective of non-comoving observers. He started by defining a rod of rest length <math>l'</math> with endpoint coordinates <math>x'_{A}=y'_{A}=0</math> and <math>x'_{B}=l',\,y'_{B}=0</math>, letting a light signal be sent from B to the origin starting at time <math>t'_{B}=-l'/c</math> and arriving at time <math>t'=0</math>. The Lorentz transformation into another frame K which is ''moving'' parallel to the x-axis gives: :<math>\begin{align}x_{B} & =\frac{x'_{B}+vt'_{B}}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=\frac{l'-\frac{v}{c}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=l'\frac{\sqrt{1-\frac{v^{2}}{c^{2}}}}{1+\frac{v}{c}}\\ t_{B} & =\frac{t'_{B}+\frac{v}{c^{2}}x'_{B}}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=\frac{-\frac{l'}{c}+\frac{v}{c^{2}}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=-\frac{l'}{c}\frac{\sqrt{1-\frac{v^{2}}{c^{2}}}}{1+\frac{v}{c}} \end{align} </math> from which he derived the Lorentz contracted length as follows: :<math>l=x_{B}+v(0-t_{B})=x_{B}-vt_{B}=l'\sqrt{1-v^{2}/c^{2}}</math> {{Lorentzbox|Text=As in the case of {{section link||Mangoldt (1910)}}, Lampa's position formula that incorporates the time-of-flight of light :<math>x_{B}=l'\frac{\sqrt{1-v^{2}/c^{2}}}{1+v/c}=l'\sqrt{\frac{1-v/c}{1+v/c}}</math>, is equivalent to equation (2) by re-interpreting <math>x_{A}=0</math> and <math>x_{B}</math> as endpoints defining the visual length of the rod.}} In order to explicitly derive the visual length of the rod, he discussed a more general case in which the endpoints A and B of the rod at rest in frame K' are given by coordinates <math>x'_{A}=0,\,y'_{A}=y'</math> and <math>x'_{B}=l',\,y'_{B}=y'</math>. So when an observer resting at the origin sees the rod at time <math>t'=0</math> , the rod's light must have been sent earlier at time <math>t'_{A}=-y'/c</math> from A and at an even earlier time <math>t'_{B}=-\sqrt{y^{\prime2}+l^{\prime2}}/c</math> from B. Applying the Lorentz transformation, he showed that the visual distance <math>\lambda</math> between A and B seen by an observer at the origin of another frame K which is ''moving'' parallel to the x-axis, is given as follows: :<math>\lambda=x_{B}-x_{A}=\frac{l'-\frac{v}{c}\left(\sqrt{y^{\prime2}+l^{\prime2}}-y'\right)}{\sqrt{1-\frac{v^{2}}{c^{2}}}}</math> He concluded: :This distance is a function of <math>v/c</math> at given <math>l'</math> and <math>y'</math>. If <math>v=0</math> or <math>v/c=0</math>, we have <math>x_{B}=l'</math> and <math>x_{A}=0</math>, thus <math>\lambda=l'</math> as it must be, because the coordinate systems always coincide at <math>v=0</math>. If we increase <math>v/c</math> beginning with value zero, then <math>x_{B}</math> decreases and finally becomes negative, while the absolute value of <math>x_{A}</math> steadily increases; <math>x_{B}-x_{A}</math> initially decreases, then reaches a minimum and then permanently increases. If <math>v/c=l'/\sqrt{y^{\prime2}+l^{\prime2}}</math>, then <math>x_{B}=0</math> and <math>x_{A}=-l'</math> and <math>\lambda</math> becomes equal to <math>l'</math>. We see that the distance of the points from which the light rays emanate as measured in system K of the stationary observer, is not at all smaller than the length of the rod measured in the coordinate system attached to it; it even becomes infinitely large if the rod moves relative to the observer with the speed of light. Yet the visual angle under which the stationary observer sees points A and B of the rod, is always finite. In frame K, he defined <math>\alpha</math> as angle of the light ray emanating from endpoint A at time <math>t_{A}</math> and <math>\beta</math> as angle of the light ray emanating from endpoint B at time <math>t_{B}</math>, and then derived the relation between the [[w:visual angle]] <math>\varphi=\beta-\alpha</math> observed in K and angle <math>\varphi'</math> observed in K' by: :<math>\begin{matrix}\sin\varphi=\sin(\beta-\alpha)=\sin\beta\cos\alpha-\cos\beta\sin\alpha\\ \sin\varphi'=\frac{l'}{\sqrt{y^{\prime2}+l^{\prime2}}},\ \cos\varphi'=\frac{y'}{\sqrt{y^{\prime2}+l^{\prime2}}}\\ \Downarrow\\ \sin\varphi=\frac{\sin\varphi'-\frac{v}{c}(1-\cos\varphi')}{1-\frac{v}{c}\sin\varphi'}\sqrt{1-\frac{v^{2}}{c^{2}}} \end{matrix}</math> He finally showed how to recover the Lorentz contracted length <math>l</math> from visual length <math>\lambda</math>: :<math>\begin{align}l & =\lambda+v\left(t_{A}-t_{B}\right)\\ & =l'\sqrt{1-\frac{v^{2}}{c^{2}}} \end{align} </math> which he rewrote in terms of angles <math>\alpha</math> and <math>\beta</math> as: :<math>\begin{align}\lambda & =y'(\tan\beta-\tan\alpha);\quad t_{A}-t_{B}=\frac{y'}{c}\left(\frac{1}{\cos\beta}-\frac{1}{\cos\alpha}\right)\\ \Rightarrow l & =y'\left[(\tan\beta-\tan\alpha)+\frac{v}{c}\left(\frac{1}{\cos\beta}-\frac{1}{\cos\alpha}\right)\right] \end{align} </math> {{Lorentzbox|Text=a) Lampa's formula for <math>\lambda</math> is more general than equation (2), producing the latter in the special case <math>y'=0</math>: :<math>\lambda=\frac{l'-\frac{v}{c}\left(\sqrt{y^{\prime2}+l^{\prime2}}-y'\right)}{\sqrt{1-\frac{v^{2}}{c^{2}}}}\underset{y'=0}{=}\frac{l'-\frac{v}{c}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=l'\sqrt{\frac{1-v/c}{1+v/c}}</math> b) He was evidently unaware of previous work on visual positions and lengths by {{section link||Grünbaum (1911)|Petzoldt (1914)|Lorentz (1914)}}. c) In a short review of Lampa's paper, [[w:Cornelius Lanczos]] (1925)<ref name=lanc25 /> described it as deriving the relation between the visual angles of a moving rod seen by resting and moving observers, as well as deriving the length of the rod from the data of its appearance.}} ===Penrose (1958/59) and Terrell (1959)=== {{section link||Petzoldt (1914)|Lorentz (1914)|Lampa (1924)}} restricted their investigations to the visual appearance of 1D rods, whereas the only early description of the visual appearance of 3D objects was given by {{section link||Plummer (1910)}} in relation to the celestial sphere based on the conformal property of aberration. However, these early investigations were evidently completely forgotten, and it took decades before those questions were taken up again: Using the conformal property of aberration, [[w:Roger Penrose]] (1958/59)<ref name=Penrose /> described the visual appearance of spheres, and discovered a completely new effect: Due to the motion of the sphere, points that were in the background become visible due to the sphere's motion, leading to the effect that the sphere appears not to be Lorentz contracted but rather rotated. Independently, [[w:James Terrell]] (1959)<ref name=Terrell /> noticed the same rotation effect in relation to 3D rods, leading him to famously declare the "invisibility of the Lorentz contraction". Independently, the special case of the visual length of 1D rods was discussed by Weinstein (1959/60).<ref name=wein60 /> A large number of follow-up papers by many authors appeared, which demonstrate the visual appearance of 1D and 3D objects in detail, see [[w:Penrose-Terrell effect]]. ==References== ===Historical references=== <references> <ref name=plum10>{{replace|{{#section:History of Topics in Special Relativity/relsource|plum10}}|*||count=1}}</ref> <ref name=mang10>{{replace|{{#section:History of Topics in Special Relativity/relsource|mang10}}|*||count=1}}</ref> <ref name=gbaum>{{replace|{{#section:History of Topics in Special Relativity/relsource|gbaum}}|*||count=1}}</ref> <ref name=laue11gru>{{replace|{{#section:History of Topics in Special Relativity/relsource|laue11gru}}|*||count=1}}</ref> <ref name=petz>{{replace|{{#section:History of Topics in Special Relativity/relsource|petz}}|*||count=1}}</ref> <ref name=einst17pop>{{replace|{{#section:History of Topics in Special Relativity/relsource|einst17pop}}|*||count=1}}</ref> <ref name=Lampa>{{replace|{{#section:History of Topics in Special Relativity/relsource|Lampa}}|*||count=1}}</ref> <ref name=lanc25>{{replace|{{#section:History of Topics in Special Relativity/relsource|lanc25}}|*||count=1}}</ref> <ref name=Penrose>{{replace|{{#section:History of Topics in Special Relativity/relsource|Penrose}}|*||count=1}}</ref> <ref name=Terrell>{{replace|{{#section:History of Topics in Special Relativity/relsource|Terrell}}|*||count=1}}</ref> <ref name=wein60>{{replace|{{#section:History of Topics in Special Relativity/relsource|wein60}}|*||count=1}}</ref> <ref name=lorentz14>{{replace|{{#section:History of Topics in Special Relativity/relsource|lorentz14}}|*||count=1}}</ref> <ref name=lorentz22>{{replace|{{#section:History of Topics in Special Relativity/relsource|lorentz22}}|*||count=1}}</ref> </references> ===Further reading=== <references group=S /> [[Category:History of special relativity]] 57onj2tgheclsuamcd0quhhwjwx002g 2835370 2835369 2026-10-01T17:20:30Z D.H 52339 /* Lorentz (1914) */ 2835370 wikitext text/x-wiki {| style="width:20%; font-size:13px;" align=right |{{../Other Topics (header)}} |} ==Early history of the Penrose–Terrell effect== {{Lorentzbox|Text={{center|Date of article creation: 19 July 2025; Last major revision: 12 December 2025}}}} If the length of an object is measured exactly at the locations of its endpoints, then its [[w:rest length]] <math>l'</math> is related to its length <math>l</math> in a relatively moving frame by the [[w:length contraction]] formula: :(1) <math>\quad l=l'\sqrt{1-v^{2}/c^{2}}</math> However, it turns out that the ''visual appearance'' of that object when photographed from a distance leads to quite different results, because optical aberration and time-of-flight effects have to be considered as well. In particular, light rays arriving simultaneously at the camera weren't emitted simultaneously from all locations at the source.<ref group=S name=space>A very detailed account of the visual appearance of moving bodies is presented on the website [https://www.spacetimetravel.org/ Space Time Travel] which is based on the German website [https://www.tempolimit-lichtgeschwindigkeit.de/ Tempolimit Lichtgeschwindigkeit], where the accompanied paper [https://www.tempolimit-lichtgeschwindigkeit.de/phantom/pdnw97.pdf Appearance of relativistically moving objects (in German)] gives the formula for the length of 1D rods, followed by descriptions of rotated cubes and spheres.</ref> ;1D rods The visual length <math>L</math> of a 1D rod that is both oriented and moving ''along'' the x-axis, and which approaches or recedes a camera that is located on the same x-axis, is given by :(2) <math>\quad\begin{matrix}L_{{\rm approach}}=\frac{l}{1-v/c}=l'\sqrt{\frac{1+v/c}{1-v/c}}\\ L_{{\rm recede}}=\frac{l}{1+v/c}=l'\sqrt{\frac{1-v/c}{1+v/c}} \end{matrix}</math> So if the 1D rod approaches it appears to be longer, if it recedes it appears to be shorter, and none of those lengths precisely matches the contraction formula (1) but rather depend on the [[w:Relativistic_Doppler_effect|w:relativistic Doppler factor]] that also appears in the [[w:Aberration (astronomy)#Relativistic explanation|w:relativistic aberration formula]]. {{Lorentzbox|Text=Formula (2) was introduced by {{section link||Petzoldt (1914)}} and in a more general way that also allows for motions along lines ''parallel'' to the x-axis by {{section link||Lorentz (1914)|Lampa (1924)}}. Even before those authors, the visual position of a ''point'' was derived by {{section link||Mangoldt (1910)}} and related to photographic images by {{section link||Grünbaum (1911)}}.}} The visual length on a photograph ''directly'' corresponds to contraction formula (1) when the moving 1D rod is oriented ''perpendicular'' to the camera's line of sight and the rod's center is exactly in the camera's line of sight at the time of light emission, because in this case the light emanating ''simultaneously'' from both ends of the moving rod will travel the same distance to the camera and therefore arrive ''simultaneously'' as well, which can be compared to the visual length of a stationary rod that was momentarily at the same position as the moving rod when light was emanated from its endpoints. {{Lorentzbox|Text=This was demonstrated by {{section link||Lorentz (1922)}}.}} In case the rod's center is ''not'' exactly in the camera's line of sight at the time of light emission, Lorentz contraction can only be detected on photographs by resorting to approximations such as making the rod's length very small with respect to the rod's distance from the camera. {{Lorentzbox|Text=This was shown by {{section link||Mangoldt (1910)|Grünbaum (1911)|Lorentz (1914)}}.}} ;3D objects It becomes more complicated when 3D objects are considered. First we notice the conformal property of the [[w:Aberration (astronomy)#Relativistic explanation|w:relativistic aberration formula]] :(3) <math>\quad\tan\frac{\phi}{2}=\sqrt{\frac{1+v/c}{1-v/c}}\tan\frac{\phi'}{2}</math> because it only changes the scale but not the shape of spherical outlines, thus the visual appearance of spheres ''remains spherical'' on camera. {{Lorentzbox|Text=This was pointed out by {{section link||Plummer (1910)}} and rediscovered by {{section link||Penrose (1958/59) and Terrell (1959)}}.}} Furthermore, light emitted on the backside of arbitrary 3D objects such as spheres, rods and cubes can reach the camera, because the object's motion frees the path of light rays that were hidden otherwise. Consequently, if the object is very far away and subtends a very small angle, it doesn't appear contracted but rather ''rotated'' by <math>\phi-\phi'</math>. {{Lorentzbox|Text=This was pointed out by {{section link||Penrose (1958/59) and Terrell (1959)}}.}} The description of visual distortions is connected to the names of Penrose and Terrell in most papers, hence it is called [[w:Penrose–Terrell effect]]/rotation or Terrell effect/rotation or Lampa–Penrose–Terrell effect. Given the historical information provided above, the expression '''Penrose-Terrell effect''' is appropriate when it comes to rotations alone; yet when it comes to the visual appearance of moving bodies in general, one should should not forget the early contributions of Plummer, Petzoldt, Lorentz, Lampa. ==Historical papers== ===Plummer (1910)=== [[w:Henry Crozier Keating Plummer]]<ref name=plum10 /> derived the following consequence from relativistic aberration: :In the first place we may consider the stereographic projection of the celestial sphere on the tangent plane perpendicular to the direction of motion. The form of the law of aberration ::<math>\tan\frac{1}{2}\phi'=\sqrt{\frac{U-v}{U+v}}\tan\frac{1}{2}\phi</math> :shows that the effect of aberration is simply to alter the ''scale'' of the projection. But the stereographic projection is a conformal representation of the sphere. Hence actual configurations on the sphere are only changed conformally by the effect of aberration, or in other words any small area is altered only in size and not in shape. We know that aberration merely changes the scale of a photograph of a small part of the sky, and the truth of this fact now becomes independent of the velocity (however large) of the observer. Also stars which appear to lie on a circle at any one time will continue to do so permanently. {{Lorentzbox|Text=Thus Plummer showed that independent of the velocity of the observer, the ''photograph'' of parts of the celestial sphere is changed by relativistic aberration only in terms of scale, not shape, thus spherical outlines remain spherical.}} ===Mangoldt (1910)=== [[w:Hans Carl Friedrich von Mangoldt]]<ref name=mang10 /> demonstrated the constancy of light speed in different frames by using the case of a light ray emitted from the origin and then traversing distance <math>-l</math> in the negative x-direction during time <math>t=l/c</math>. A ''moving'' marker momentarily co-located at position <math>-l</math> at time <math>t</math> will indicate the Lorentz transformed value :<math>x'=\beta(x-vt)=-\beta\left(l+v\frac{l}{c}\right)=-\beta l\left(1+\frac{v}{c}\right)</math> and a momentarily co-located moving clock indicates :<math>t'=\beta\left(-\frac{v}{c^{2}}x+t\right)=\beta\left(\frac{v}{c^{2}}l+\frac{l}{c}\right)=\beta\frac{l}{c}\left(1+\frac{v}{c}\right)</math> where <math>\beta=1/\sqrt{1-v^{2}/c^{2}}</math> was used by him as Lorentz factor, proving <math>x'/t'=-c</math> as it should be. At the end of his paper, he alluded to the possibility of using ''photographs'' of ''sufficiently small areas'' at ''sufficient distance'' from the camera, which should directly provide an ''approximately'' correct image of relativistic effects such as length contraction and time dilation as indicated by markers and clocks. {{Lorentzbox|Text=a) We see that his position equation that incorporates the time-of-flight of light (using modern notation <math>\gamma</math> for the Lorentz factor) :<math>x'=-\gamma l\left(1+\frac{v}{c}\right)=l\sqrt{\frac{1+v/c}{1-v/c}}</math>, is formally equivalent to equation (2), and it's easy to re-interpret his result in terms of visual lengths: We introduce a rod whose rest length <math>l'</math> is defined by coordinate <math>x'</math> as left endpoint and the origin as right endpoint, in which case Mangoldt's distance <math>l</math> is identical with the rod's visual length <math>L</math> as photographed at time <math>t=l/c</math> by a camera located at position <math>-l</math>. b) Ironically, even though he was in possession of the optical position formula that incorporates the time-of-flight of light, he only discussed an ''approximate'' case in order to directly demonstrate length contraction and time dilation on photographic images ''without'' considering time-of-flight delays, which was clarified by {{section link||Grünbaum (1911)}}. Anyway, Mangoldt's restriction to an approximate case shows, that he was well aware that an exact treatment requires the consideration of time-of-flight delays.}} ===Grünbaum (1911)=== In a follow-up paper to {{section link||Mangoldt (1910)}}, the physicist [[w:de:Fritz Grünbaum (Physiker)|w:Fritz Grünbaum]]<ref name=gbaum /> discussed the ''photographic image'' of distant points. He described a marker (indicating its spatial position) and a co-located clock (indicating its time) that are at relative rest with respect to a photographic apparatus, and another marker/clock pair in relative motion with respect to that apparatus. When both marker/clock pairs meet each other at point P, the apparatus located at point R makes a photo of them. In the rest frame of the apparatus, <math>l</math> is the distance from P to R, and T is the time at which the image was created on the photographic plate. On that image, the resting marker indicates its spatial coordinate <math>x_{r}</math> while the resting clock indicates its time <math>t_{r}=T-l/c</math> since light took some time to traverse distance <math>l</math>. In order to find out which values are indicated on the photographic image of the ''moving'' marker/clock pair, he used the Lorentz transformation (with <math>\beta</math> as Lorentz factor): :<math>\begin{matrix}x'_{r}=\beta\left(x_{r}-vt_{r}\right)\Rightarrow\beta\left[x-v\left(T-\frac{l}{c}\right)\right]\\ t'_{r}=\beta\left(t_{r}-\frac{v}{c^{2}}x_{r}\right)\Rightarrow\beta\left[\left(T-\frac{l}{c}\right)-\frac{v}{c^{2}}x\right]\\ \left[\beta=\frac{1}{\sqrt{1-v^{2}/c^{2}}},\ x_{r}=x,\ t_{r}=T-\frac{l}{c}\right] \end{matrix}</math> which he summarized in the following table: {| cellpadding="10" |- |On the image <br />of the apparatus: |style="border-left:1px solid black" |Stationary marker: <math>x,\ y=0</math> Stationary clock: <math>T-\frac{l}{c}</math> Moving marker: <math>\beta\left[x-v\left(T-\frac{l}{c}\right)\right]</math> Moving clock: <math>\beta\left[\left(T-\frac{l}{c}\right)-\frac{v}{c^{2}}x\right]</math> |} He then described the symmetrical case when the photographic image of P is made by a ''moving'' observer B, discussed the special cases <math>T=T'=0</math> , which together with <math>x=0</math> and <math>l=y</math> and by considering time-of-flight effects, allows to indirectly recover both length contraction and time dilation as well as their symmetry by analyzing the data given on the images. Finally he clarified Mangoldt's claim according to whom one can directly demonstrate length contraction ''without'' considering time-of-flight effects: He showed that this can only be done if one strictly follows Mangoldt's requirement that the rod length <math>x</math> must be very small compared to distance <math>y</math>, which indeed produces the Lorentz contraction formula <math>x'=\beta x</math> because the differences in the emission times at the endpoints are so small that they approximately happened simultaneously. {{Lorentzbox|Text=a) His formula for the visual ''position'' of a ''photographed'' marker in motion easily allows us to derive the visual ''length'' between two points: We place R to the origin <math>x_{0}=0</math> so that point P is at position <math>x=l</math>, thus we can interpret R and P as endpoints of a horizontally aligned and moving rod measured at time <math>T=0</math>, which gives (using modern notation <math>\gamma</math> for the Lorentz factor): :<math>x'_{r}=\gamma\left[x-v\left(T-\frac{l}{c}\right)\right]\underset{{x=l\atop T=0}}{=}\gamma\left[l-\frac{v}{c}l\right]=l\sqrt{\frac{1-v/c}{1+v/c}}</math> equivalent to equation (2) by identifying his length <math>l</math> with visual length <math>L</math> and coordinate <math>x'_{r}</math> as the right endpoint of a rod of rest length <math>l'</math> whose left endpoint is at the origin. So Grünbaum correctly incorporated time-of-flight effects in order to derive the visual ''position'' of points with respect to photographs. Yet he treated the visual ''length'' of moving rods only in approximation while clarifying Mangoldt's statements. b) In a short review of Grünbaum's paper, [[w:Max von Laue]] (1911)<ref name=laue11gru /> described it as using photographic images to demonstrate Lorentz contraction. }} ===Petzoldt (1914)=== In an otherwise philosophical analysis of relativity, [[w:Joseph Petzoldt]]<ref name=petz /> demonstrated the following consequence: :The perspectivistic shape changes of bodies whose velocity is comparable to that of light, do not appear to have been investigated yet. [..] The image of an object, which is generated on the retina of the eye or on the photographic plate - as a snapshot - is produced by light coming from all the points of the object in question, but it wasn't sent at the same time: all of the light that contributes to the production of the image arrives simultaneously with the light that originated from those points of the object that were closest to the eye or plate; the further the object's point is from the plate or eye, the sooner it must send its contribution of light. The result is that the image of a receding or approaching object having a large speed comparable to that of light, does not correspond to the image of the same object if it were at rest relative to the eye or plate, but rather gives the impression that it originated from a shorter or longer object within that radius of distance. In case the object is receding from the eye or plate, the light contributed from the most distant points would have been sent later, in the case of approach it would have been sent earlier than in the state of rest. A simple calculation that takes into account the Lorentz contraction, results in the fact that the object in question whose physical length is <math>l\sqrt{1-\tfrac{v^{2}}{c^{2}}}</math>, where <math>l</math> is the length for the "co-moving" observer, would have to be assessed on the basis of this photographic momentary image as having the perspectivistic moving length: ::<math>l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c+v}\qquad</math> or <math>\qquad l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c-v}</math>, :depending on the whether the object recedes or approaches the eye or plate. {{Lorentzbox|Text=a) Petzoldt correctly derived the visual length of moving 1D rods, his results being equivalent to equation (2): :<math>\begin{matrix}l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c-v}=l\sqrt{\frac{1+v/c}{1-v/c}}\\ l\sqrt{1-\frac{v^{2}}{c^{2}}}\cdot\frac{c}{c+v}=l\sqrt{\frac{1-v/c}{1+v/c}} \end{matrix}</math> b) As explained in [[w:Joseph Petzoldt|Petzoldt's Wikipedia article]], it was [[w:Albert Einstein]] himself who publicly recommended Petzoldt's 1914 paper in a newspaper article and privately praised it by letter, which implies that by 1914, Einstein should have been aware of the pitfalls that arise when describing photographs of Lorentz contracted bodies. However, in the [[s:Relativity (1931)/Appendix 1|s:first appendix]] to his popular book [[w:Relativity: The Special and the General Theory]] that was added to the third edition from 1918 and still remains in modern editions,<ref name=einst17pop /> he seems to have overlooked this fact. Einstein argued that <math>\Delta x=1/a</math> is the length indicated on a "snapshot" or "instantaneous photograph" of a unit length at rest in K' that was taken from system K at time <math>t=0</math>, and that <math>\Delta x'=a\left(1-v^{2}/c^{2}\right)</math> is the length indicated on a snapshot of a unit length at rest in K that was taken from system K' at time <math>t'=0</math>; since symmetry requires that <math>\Delta x=\Delta x'</math>, he concluded that <math>a^{2}=1/\left(1-v^{2}/c^{2}\right)</math>. If we plug his result into his snapshot length equations we get <math>\Delta x=\sqrt{1-v^{2}/c^{2}}</math> and symmetrically <math>\Delta x'=\sqrt{1-v^{2}/c^{2}}</math>, identical to the Lorentz contraction of unit rest lengths. Yet while Einstein's derivation is correct, his choice of visualizing this result in terms of "snapshots" can be misleading since one has to consider time-of-flight effects which leads to visual deviations in most cases. }} ===Lorentz (1914)=== [[File:Lorentz1914-2.png|250px|right]] [[w:Hendrik Lorentz]] (March 1914)<ref name=lorentz14 /> described two rulers along line EF, one at rest with respect to observer A having length <math>l'=l</math>, and the other moving with respect to A with velocity <math>v</math> having contracted length <math>l'=l/a</math> (where <math>a</math> is the Lorentz factor). He then derived a general formula for the approximated visual length <math>s</math> of the rods as a function of <math>l'</math>, using an photographic apparatus moving with velocity <math>w</math>. On the screen of the apparatus there is a small slot D situated at vertical distance L from E, and below there is a photographic plate at vertical distance <math>\lambda</math> from D. Then slot D is opened for one moment, during which it is passed by optical signals from endpoints F and G of the rods (where <math>FG=l'</math>), reaching points f and g on the plate. Since the signals reaching D at the same time are sent from different locations, they were not emitted simultaneously. Assuming the signal from F was sent at time <math>t_{0}</math> at position <math>x_{0}</math> after which it traverses distance <math>\sqrt{L^{2}+x_{0}^{2}}</math> to D, it follows that the signal from G was sent at an earlier time <math>t_{0}+\tau</math> at position <math>x_{1}=x_{0}+l'+v\tau</math> after which it traverses distance <math>\sqrt{L^{2}+\left(x_{0}+l'+v\tau\right)^{2}}</math> to D. Thus the value of <math>\tau</math> is given by :<math>\sqrt{L^{2}+\left(x_{0}+l'+v\tau\right)^{2}}-\sqrt{L^{2}+x_{0}^{2}}=-c\tau</math> or using angle <math>EDF=\phi_{0}</math> and assuming very large L by which terms containing <math>l'^{2}</math> and <math>\tau^{2}</math> can be neglected: :<math>\tau=-\frac{\sin\phi_{0}}{c+v\sin\phi_{0}}l'</math>, thus <math>x_{1}=x_{0}+\frac{cl'}{c+v\sin\phi_{0}}</math>. After deriving the position of points f and g on the plate, and under consideration that the plate was moving with velocity <math>w</math>, he obtained the general formula representing the approximated visual length of rods: :<math>s=\frac{\lambda}{L}\frac{c+w\sin\phi_{0}}{c+v\sin\phi_{0}}l'</math>. The visual length <math>s_{1}</math> of the resting rod follows by plugging in <math>v=0</math> and <math>l'=l</math>, whereas visual length <math>s_{2}</math> of the moving rod follows by plugging in <math>l'=l/a</math> (where <math>a</math> is the Lorentz factor), thus :<math>\frac{s_{1}}{s_{2}}=\left(1+\frac{v}{c}\sin\phi_{0}\right)a</math>. He showed that the case <math>\phi_{0}=0</math> allows to recover the Lorentz contraction formula :<math>\frac{s_{1}}{s_{2}}=a</math>, which is possible because in this approximation neglecting terms containing <math>l'^{2}</math>, one can pretend as if the emission of the light signals at F and G happened simultaneously. {{Lorentzbox|Text=a) Setting <math>\phi_{0}=\pi/2</math> in the case of 90 degrees, his formula produces (with <math>a</math> as Lorentz factor): :<math>\frac{s_{1}}{s_{2}}=\left(1+\frac{v}{c}\right)a=\sqrt{\frac{1+v/c}{1-v/c}}</math> equivalent to the longitudinal visual length formula (2), independently derived by {{section link||Petzoldt (1914)}}. b) Lorentz's last case <math>\phi_{0}=0</math> agrees with {{section link||Mangoldt (1910)|Grünbaum (1911)}} who argued that Lorentz contraction can be recovered from the data on photographs under certain approximations.}} ===Lorentz (1922)=== In 1922 (published 1927),<ref name=lorentz22 /> [[w:Hendrik Lorentz]] simplified his earlier treatment of 1914 by writing: [[File:Lorentz1927-31.png|250px|right]] :Let there be two “equal” rods P and Q, placed along the line AB parallel to OZ, and let the first be at rest in x, y, z, t, the other in x’, y’, z’, t’. The screen CD coincides with the plane YOZ, the distance OK being <math>p</math>, and EF is the photographic plate, at a distance <math>OM=q</math> behind the screen. :In A’s experiment the screen and the photographic plate are at rest in the system x, y, z, the pinhole being constantly at the origin O of those coordinates. We shall suppose it to be opened for an instant at time <math>t=0</math>, and we shall define the “effective” position of a moving point by the condition that light emitted by the point in that position shall reach the hole O just when it is opened; the time at which the effective position is reached may be called the effective time. We shall denote by <math>2l</math> the length of the rod P in the system x, y, z, so that in the same system <math>2a/l</math> [with <math>a</math> as Lorentz factor] is the length of Q. For the sake of simplicity we shall suppose <math>l</math> to be so small that terms with <math>l^{2}</math> may be neglected. :Now A must be sure that he compares ''simultaneous'' positions of the ends of the moving rod Q. He can satisfy this condition by arranging the experiment in such a way that the middle point of Q passes through <math>K(z=0)</math> at the time <math>-p/c</math>. We shall further assume that the middle point of P always has this position. :It is easily seen that in this first experiment the images of the two rods have the lengths <math>2\tfrac{q}{p}l</math> and <math>2\tfrac{q}{p}\tfrac{l}{a}</math>, the second being <math>a</math> times shorter than the first. {{Lorentzbox|Text=a) Lorentz's method, in which both endpoints of the rod have the same distance to hole O, can indeed accurately represent the different lengths of resting and moving 1D rods on a photograph. b) As later shown by {{section link||Penrose (1958/59) and Terrell (1959)}}, this method doesn't work anymore when 3D objects are considered.}} ===Lampa (1924)=== [[w:Anton Lampa]]<ref name=Lampa /> devoted an entire paper to the question of the visual length of moving rods. He pointed out, that the relativistic length contraction formula doesn't say anything about the visual appearance of moving rods from the perspective of non-comoving observers. He started by defining a rod of rest length <math>l'</math> with endpoint coordinates <math>x'_{A}=y'_{A}=0</math> and <math>x'_{B}=l',\,y'_{B}=0</math>, letting a light signal be sent from B to the origin starting at time <math>t'_{B}=-l'/c</math> and arriving at time <math>t'=0</math>. The Lorentz transformation into another frame K which is ''moving'' parallel to the x-axis gives: :<math>\begin{align}x_{B} & =\frac{x'_{B}+vt'_{B}}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=\frac{l'-\frac{v}{c}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=l'\frac{\sqrt{1-\frac{v^{2}}{c^{2}}}}{1+\frac{v}{c}}\\ t_{B} & =\frac{t'_{B}+\frac{v}{c^{2}}x'_{B}}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=\frac{-\frac{l'}{c}+\frac{v}{c^{2}}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=-\frac{l'}{c}\frac{\sqrt{1-\frac{v^{2}}{c^{2}}}}{1+\frac{v}{c}} \end{align} </math> from which he derived the Lorentz contracted length as follows: :<math>l=x_{B}+v(0-t_{B})=x_{B}-vt_{B}=l'\sqrt{1-v^{2}/c^{2}}</math> {{Lorentzbox|Text=As in the case of {{section link||Mangoldt (1910)}}, Lampa's position formula that incorporates the time-of-flight of light :<math>x_{B}=l'\frac{\sqrt{1-v^{2}/c^{2}}}{1+v/c}=l'\sqrt{\frac{1-v/c}{1+v/c}}</math>, is equivalent to equation (2) by re-interpreting <math>x_{A}=0</math> and <math>x_{B}</math> as endpoints defining the visual length of the rod.}} In order to explicitly derive the visual length of the rod, he discussed a more general case in which the endpoints A and B of the rod at rest in frame K' are given by coordinates <math>x'_{A}=0,\,y'_{A}=y'</math> and <math>x'_{B}=l',\,y'_{B}=y'</math>. So when an observer resting at the origin sees the rod at time <math>t'=0</math> , the rod's light must have been sent earlier at time <math>t'_{A}=-y'/c</math> from A and at an even earlier time <math>t'_{B}=-\sqrt{y^{\prime2}+l^{\prime2}}/c</math> from B. Applying the Lorentz transformation, he showed that the visual distance <math>\lambda</math> between A and B seen by an observer at the origin of another frame K which is ''moving'' parallel to the x-axis, is given as follows: :<math>\lambda=x_{B}-x_{A}=\frac{l'-\frac{v}{c}\left(\sqrt{y^{\prime2}+l^{\prime2}}-y'\right)}{\sqrt{1-\frac{v^{2}}{c^{2}}}}</math> He concluded: :This distance is a function of <math>v/c</math> at given <math>l'</math> and <math>y'</math>. If <math>v=0</math> or <math>v/c=0</math>, we have <math>x_{B}=l'</math> and <math>x_{A}=0</math>, thus <math>\lambda=l'</math> as it must be, because the coordinate systems always coincide at <math>v=0</math>. If we increase <math>v/c</math> beginning with value zero, then <math>x_{B}</math> decreases and finally becomes negative, while the absolute value of <math>x_{A}</math> steadily increases; <math>x_{B}-x_{A}</math> initially decreases, then reaches a minimum and then permanently increases. If <math>v/c=l'/\sqrt{y^{\prime2}+l^{\prime2}}</math>, then <math>x_{B}=0</math> and <math>x_{A}=-l'</math> and <math>\lambda</math> becomes equal to <math>l'</math>. We see that the distance of the points from which the light rays emanate as measured in system K of the stationary observer, is not at all smaller than the length of the rod measured in the coordinate system attached to it; it even becomes infinitely large if the rod moves relative to the observer with the speed of light. Yet the visual angle under which the stationary observer sees points A and B of the rod, is always finite. In frame K, he defined <math>\alpha</math> as angle of the light ray emanating from endpoint A at time <math>t_{A}</math> and <math>\beta</math> as angle of the light ray emanating from endpoint B at time <math>t_{B}</math>, and then derived the relation between the [[w:visual angle]] <math>\varphi=\beta-\alpha</math> observed in K and angle <math>\varphi'</math> observed in K' by: :<math>\begin{matrix}\sin\varphi=\sin(\beta-\alpha)=\sin\beta\cos\alpha-\cos\beta\sin\alpha\\ \sin\varphi'=\frac{l'}{\sqrt{y^{\prime2}+l^{\prime2}}},\ \cos\varphi'=\frac{y'}{\sqrt{y^{\prime2}+l^{\prime2}}}\\ \Downarrow\\ \sin\varphi=\frac{\sin\varphi'-\frac{v}{c}(1-\cos\varphi')}{1-\frac{v}{c}\sin\varphi'}\sqrt{1-\frac{v^{2}}{c^{2}}} \end{matrix}</math> He finally showed how to recover the Lorentz contracted length <math>l</math> from visual length <math>\lambda</math>: :<math>\begin{align}l & =\lambda+v\left(t_{A}-t_{B}\right)\\ & =l'\sqrt{1-\frac{v^{2}}{c^{2}}} \end{align} </math> which he rewrote in terms of angles <math>\alpha</math> and <math>\beta</math> as: :<math>\begin{align}\lambda & =y'(\tan\beta-\tan\alpha);\quad t_{A}-t_{B}=\frac{y'}{c}\left(\frac{1}{\cos\beta}-\frac{1}{\cos\alpha}\right)\\ \Rightarrow l & =y'\left[(\tan\beta-\tan\alpha)+\frac{v}{c}\left(\frac{1}{\cos\beta}-\frac{1}{\cos\alpha}\right)\right] \end{align} </math> {{Lorentzbox|Text=a) Lampa's formula for <math>\lambda</math> is more general than equation (2), producing the latter in the special case <math>y'=0</math>: :<math>\lambda=\frac{l'-\frac{v}{c}\left(\sqrt{y^{\prime2}+l^{\prime2}}-y'\right)}{\sqrt{1-\frac{v^{2}}{c^{2}}}}\underset{y'=0}{=}\frac{l'-\frac{v}{c}l'}{\sqrt{1-\frac{v^{2}}{c^{2}}}}=l'\sqrt{\frac{1-v/c}{1+v/c}}</math> b) He was evidently unaware of previous work on visual positions and lengths by {{section link||Grünbaum (1911)|Petzoldt (1914)|Lorentz (1914)}}. c) In a short review of Lampa's paper, [[w:Cornelius Lanczos]] (1925)<ref name=lanc25 /> described it as deriving the relation between the visual angles of a moving rod seen by resting and moving observers, as well as deriving the length of the rod from the data of its appearance.}} ===Penrose (1958/59) and Terrell (1959)=== {{section link||Petzoldt (1914)|Lorentz (1914)|Lampa (1924)}} restricted their investigations to the visual appearance of 1D rods, whereas the only early description of the visual appearance of 3D objects was given by {{section link||Plummer (1910)}} in relation to the celestial sphere based on the conformal property of aberration. However, these early investigations were evidently completely forgotten, and it took decades before those questions were taken up again: Using the conformal property of aberration, [[w:Roger Penrose]] (1958/59)<ref name=Penrose /> described the visual appearance of spheres, and discovered a completely new effect: Due to the motion of the sphere, points that were in the background become visible due to the sphere's motion, leading to the effect that the sphere appears not to be Lorentz contracted but rather rotated. Independently, [[w:James Terrell]] (1959)<ref name=Terrell /> noticed the same rotation effect in relation to 3D rods, leading him to famously declare the "invisibility of the Lorentz contraction". Independently, the special case of the visual length of 1D rods was discussed by Weinstein (1959/60).<ref name=wein60 /> A large number of follow-up papers by many authors appeared, which demonstrate the visual appearance of 1D and 3D objects in detail, see [[w:Penrose-Terrell effect]]. ==References== ===Historical references=== <references> <ref name=plum10>{{replace|{{#section:History of Topics in Special Relativity/relsource|plum10}}|*||count=1}}</ref> <ref name=mang10>{{replace|{{#section:History of Topics in Special Relativity/relsource|mang10}}|*||count=1}}</ref> <ref name=gbaum>{{replace|{{#section:History of Topics in Special Relativity/relsource|gbaum}}|*||count=1}}</ref> <ref name=laue11gru>{{replace|{{#section:History of Topics in Special Relativity/relsource|laue11gru}}|*||count=1}}</ref> <ref name=petz>{{replace|{{#section:History of Topics in Special Relativity/relsource|petz}}|*||count=1}}</ref> <ref name=einst17pop>{{replace|{{#section:History of Topics in Special Relativity/relsource|einst17pop}}|*||count=1}}</ref> <ref name=Lampa>{{replace|{{#section:History of Topics in Special Relativity/relsource|Lampa}}|*||count=1}}</ref> <ref name=lanc25>{{replace|{{#section:History of Topics in Special Relativity/relsource|lanc25}}|*||count=1}}</ref> <ref name=Penrose>{{replace|{{#section:History of Topics in Special Relativity/relsource|Penrose}}|*||count=1}}</ref> <ref name=Terrell>{{replace|{{#section:History of Topics in Special Relativity/relsource|Terrell}}|*||count=1}}</ref> <ref name=wein60>{{replace|{{#section:History of Topics in Special Relativity/relsource|wein60}}|*||count=1}}</ref> <ref name=lorentz14>{{replace|{{#section:History of Topics in Special Relativity/relsource|lorentz14}}|*||count=1}}</ref> <ref name=lorentz22>{{replace|{{#section:History of Topics in Special Relativity/relsource|lorentz22}}|*||count=1}}</ref> </references> ===Further reading=== <references group=S /> [[Category:History of special relativity]] 64zx8ti1ou5zks7b0jiy2yehkw59e1i 0 326060 2835334 2835320 2026-10-01T12:25:26Z Amélie E. Pereira 3042711 /* Ontology */ 2835334 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]])<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref>. Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and a history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} e8qlmj0isp3176slmetxdudyvnv0gye 2835337 2835334 2026-10-01T12:37:57Z Amélie E. Pereira 3042711 /* Wikimedia projects */ 2835337 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources"<ref>{{Cite journal|last=Vanegas-Cantarero|first=María M.|date=2020-12-01|title=Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries|url=https://www.wikidata.org/wiki/Q137901196|journal=Energy Research & Social Science|language=English|volume=70|doi=10.1016/J.ERSS.2020.101716}}</ref>. Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 6rc9t1ajvu9nzn8x54v1tfuk7ecvy4j 2835338 2835337 2026-10-01T12:42:11Z Amélie E. Pereira 3042711 /* Quantification */ 2835338 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite journal|last=Veelen|first=Bregje van|last2=Horst|first2=Dan van der|date=2018-12-01|title=What is energy democracy? Connecting social science energy research and political theory|url=https://www.wikidata.org/wiki/Q129652515|journal=Energy Research & Social Science|language=English|volume=46|pages=19–28|doi=10.1016/J.ERSS.2018.06.010}}</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 0upv2tckdrdngklpmtldejcegkvo4vi 2835340 2835338 2026-10-01T12:43:18Z Amélie E. Pereira 3042711 /* Precision */ 2835340 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name=":8">{{Cite web|url=https://arxiv.org/abs/2512.12260v1|title=A Multi-Axial Mindset for Ontology Design Lessons from Wikidata's Polyhierarchical Structure|last=Doğan|first=Ege Atacan|last2=Patel-Schneider|first2=Peter F.|date=2025-12-13|website=arXiv.org|language=en|access-date=2026-05-26}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} hggjgy2tntjvcyfxi2924lppitzdt5w 2835341 2835340 2026-10-01T12:51:15Z Amélie E. Pereira 3042711 /* Contradictions */ 2835341 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name=":8" /> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} s64tmp91b14hks9zkoi86sjptz1w1tt 2835342 2835341 2026-10-01T12:51:39Z Amélie E. Pereira 3042711 2835342 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}.</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}.</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated<ref name="VrandečićKrötzsch2014"/><ref>{{Cite journal|last=Zangerle|first=Eva|last2=Gassler|first2=Wolfgang|last3=Pichl|first3=Martin|last4=Steinhauser|first4=Stefan|last5=Specht|first5=Günther|date=2016-08-17|title=An Empirical Evaluation of Property Recommender Systems for Wikidata and Collaborative Knowledge Bases|url=https://dl.acm.org/doi/10.1145/2957792.2957804|journal=Proceedings of the 12th International Symposium on Open Collaboration|series=OpenSym '16|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=18|pages=1–8|doi=10.1145/2957792.2957804|isbn=978-1-4503-4451-7}}</ref>. Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} phc3kx5w8begwuq0wjqyr210gzd22r7 2835343 2835342 2026-10-01T12:55:23Z Amélie E. Pereira 3042711 /* Wikimedia projects */ 2835343 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite web|url=http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html|title=Global scientific output doubles every nine years : News blog|website=blogs.nature.com|language=en-US|access-date=2026-06-23}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} q8l0rsiwiif9bgp89udvd37zpfizkv9 2835344 2835343 2026-10-01T13:01:06Z Amélie E. Pereira 3042711 /* The problem of academic information overload */ 2835344 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research<ref>{{Cite journal|last=Vrandečić|first=Denny|last2=Pintscher|first2=Lydia|last3=Krötzsch|first3=Markus|date=2023-04-30|title=Wikidata: The Making Of|url=https://dl.acm.org/doi/10.1145/3543873.3585579|journal=Companion Proceedings of the ACM Web Conference 2023|series=WWW '23 Companion|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=615–624|doi=10.1145/3543873.3585579|isbn=978-1-4503-9419-2}}</ref>. Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} f6ze8cd6onw013l6qgkhyni0nxbpjs6 2835346 2835344 2026-10-01T13:07:08Z Amélie E. Pereira 3042711 /* Use of Wikidata and Wikiversity for research */ 2835346 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}.</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}.</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}.</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} q4dtxilx7rhzfy2l5l3eo497vqxox3v 2835350 2835346 2026-10-01T14:56:25Z Amélie E. Pereira 3042711 /* Quality assessment */ 2835350 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite journal|last=Droubi|first=Sufyan|last2=Heffron|first2=Raphael|last3=McCauley|first3=Darren|date=2022-04-01|title=A critical review of energy democracy: A failure to deliver justice?|url=https://www.wikidata.org/wiki/Q137901182|journal=Energy Research & Social Science|volume=86|pages=4|doi=10.1016/J.ERSS.2021.102444}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} c56oojkt9ujhae6k7psae2fqawue91b 2835351 2835350 2026-10-01T15:03:16Z Amélie E. Pereira 3042711 /* Testing concept modelling on {{Wikidata entity link|Q14944319}} */ 2835351 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite journal|last=Makowski|first=Piotr Tomasz|date=2021-10|title=Optimizing Concepts: Conceptual Engineering in the Field of Management—The Case of Routines Research|url=http://journals.aom.org/doi/full/10.5465/amr.2019.0252|journal=Academy of Management Review|language=en|volume=46|issue=4|pages=702–724|doi=10.5465/amr.2019.0252|issn=0363-7425}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} rtzibsf83a4srfij8bhjoyefewxt758 2835352 2835351 2026-10-01T15:12:31Z Amélie E. Pereira 3042711 /* Conceptual modelling */ 2835352 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name=":21">{{Cite journal|last=Gioia|first=Dennis A.|last2=Corley|first2=Kevin G.|last3=Hamilton|first3=Aimee L.|date=2013-01|title=Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology|url=https://journals.sagepub.com/doi/10.1177/1094428112452151|journal=Organizational Research Methods|language=en|volume=16|issue=1|pages=15–31|doi=10.1177/1094428112452151|issn=1094-4281}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name=":21" />R.esearchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite book|url=https://link.springer.com/10.1007/978-3-031-01919-7_4|title=Causal Loop Diagrams|last=Barbrook-Johnson|first=Pete|last2=Penn|first2=Alexandra S.|date=2022|publisher=Springer International Publishing|isbn=978-3-031-01833-6|location=Cham|pages=47–59|language=en|doi=10.1007/978-3-031-01919-7_4}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} qwo76adqpaz31onwc9da2bafo1aymjk 2835354 2835352 2026-10-01T15:19:48Z Amélie E. Pereira 3042711 /* Causal diagrams */ 2835354 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite journal|last=Corbin|first=Juliet|last2=Strauss|first2=Anselm|date=1990-12-01|title=Grounded Theory Research: Procedures, Canons and Evaluative Criteria|url=https://www.degruyter.com/document/doi/10.1515/zfsoz-1990-0602/html|journal=Zeitschrift für Soziologie|language=en|volume=19|issue=6|pages=418–427|doi=10.1515/zfsoz-1990-0602|issn=2366-0325}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} lsv4vw41pbtshhrhwyndgfues22obiw 2835355 2835354 2026-10-01T15:21:42Z Amélie E. Pereira 3042711 /* Thematic networks */ 2835355 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name=":7">{{Cite journal|last=Attride-Stirling|first=Jennifer|date=2001-12|title=Thematic networks: an analytic tool for qualitative research|url=https://journals.sagepub.com/doi/10.1177/146879410100100307|journal=Qualitative Research|language=en|volume=1|issue=3|pages=385–405|doi=10.1177/146879410100100307|issn=1468-7941}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name=":7" />. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} hxe648683rdajlpq6yu4yndl21elfc6 2835356 2835355 2026-10-01T15:24:28Z Amélie E. Pereira 3042711 /* Thematic networks */ 2835356 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite journal|last=Woltjer|first=Pieter E.|last2=Zandhuis|first2=Ivo|last3=Coret|first3=Bob|last4=Lindeman|first4=Mark|last5=Balkenende|first5=Jeroen D.|last6=Zijdeman|first6=Richard L.|last7=Mourits|first7=Rick J.|date=2024-10-17|title=Persons in Context. A Model to Represent Observations and Reconstructions of Historical Persons in Linked Data|url=https://hlcs.nl/article/view/19312|journal=Historical Life Course Studies|language=en|volume=14|pages=105–125|doi=10.51964/hlcs19312|issn=2352-6343}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} sf6ui5si89pgag3puz8mdc7d402ydfz 2835357 2835356 2026-10-01T15:27:13Z Amélie E. Pereira 3042711 /* Knowledge graphs for research */ 2835357 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite journal|last=Stark|first=Anthony|last2=Gale|first2=Fred|last3=Murphy-Gregory|first3=Hannah|date=2023-05-05|title=Just Transitions’ Meanings: A Systematic Review|url=https://www.wikidata.org/wiki/Q137210229|journal=Society and Natural Resources|volume=36|issue=10|pages=1277–1297|doi=10.1080/08941920.2023.2207166}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite journal|last=Jenkins|first=Kirsten|last2=McCauley|first2=Darren|last3=Heffron|first3=Raphael|last4=Stephan|first4=Hannes|last5=Rehner|first5=Robert|date=2016-01-01|title=Energy justice: A conceptual review|url=https://www.wikidata.org/wiki/Q137210566|journal=Energy Research & Social Science|volume=11|pages=174–182|doi=10.1016/J.ERSS.2015.10.004}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} f03pp1v83wlde2b4ex1n0g90a14mp8r 2835358 2835357 2026-10-01T15:28:41Z Amélie E. Pereira 3042711 /* Database search */ 2835358 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite journal|last=Lewis|first=John Kennedy|date=2016|title=Using ATLAS.ti to Facilitate Data Analysis for a Systematic Review of Leadership Competencies in the Completion of a Doctoral Dissertation|url=https://www.ssrn.com/abstract=2850726|journal=SSRN Electronic Journal|language=en|doi=10.2139/ssrn.2850726|issn=1556-5068}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 2qoqi0210yl9j9sjw8ar4ys7o91zstf 2835359 2835358 2026-10-01T15:31:01Z Amélie E. Pereira 3042711 /* Concept maps */ 2835359 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite Q|Q134545591}}</ref> allowing to synthetize theoretical statements about relationship between concepts<ref>{{Cite journal|last=Panniers|first=Teresa L|last2=Feuerbach|first2=Renee Daiuta|last3=Soeken|first3=Karen L|date=2003-08-01|title=Methods in informatics: using data derived from a systematic review of health care texts to develop a concept map for use in the neonatal intensive care setting|url=https://www.sciencedirect.com/science/article/pii/S1532046403000911|journal=Journal of Biomedical Informatics|series=Building Nursing Knowledge through Informatics: From Concept Representation to Data Mining|volume=36|issue=4|pages=232–239|doi=10.1016/j.jbi.2003.09.010|issn=1532-0464}}</ref>. They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 8g6t2fucagq2zv369y2pcjrm6crjzbr 2835360 2835359 2026-10-01T15:32:25Z Amélie E. Pereira 3042711 /* Concept maps */ 2835360 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}<ref>{{Cite journal|last=Paré|first=Guy|last2=Trudel|first2=Marie-Claude|last3=Jaana|first3=Mirou|last4=Kitsiou|first4=Spyros|date=2015-03|title=Synthesizing information systems knowledge: A typology of literature reviews|url=https://linkinghub.elsevier.com/retrieve/pii/S0378720614001116|journal=Information & Management|language=en|volume=52|issue=2|pages=183–199|doi=10.1016/j.im.2014.08.008}}</ref>. After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite Q|Q134545591}}</ref> allowing to synthetize theoretical statements about relationship between concepts.<ref>{{Cite Q|Q30884964}}</ref> They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} 0m7hygnlbiukoftosrsv8hn00y89kf5 2835361 2835360 2026-10-01T15:35:24Z Amélie E. Pereira 3042711 /* Adding {{Wikidata entity link|P8363}} */ 2835361 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}.<ref>{{Cite Q|Q115443776}}</ref> After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite journal|last=Nielsen|first=Finn Årup|last2=Lyhne|first2=Ivar|last3=Garigliotti|first3=Dario|last4=Butzbach|first4=Annika|last5=Ravn Boess|first5=Emilia|last6=Hose|first6=Katja|last7=Kørnøv|first7=Lone|date=2023|title=Environmental impact assessment reports in Wikidata and a Wikibase|url=https://repositum.tuwien.at/handle/20.500.12708/193492|language=en|publisher=CEUR-WS.org|volume=3443|pages=1–8|doi=10.34726/5421}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite Q|Q134545591}}</ref> allowing to synthetize theoretical statements about relationship between concepts.<ref>{{Cite Q|Q30884964}}</ref> They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} l8jgnnlzyi67a6e6zlj8wmgo0oneg1a 2835362 2835361 2026-10-01T15:40:36Z Amélie E. Pereira 3042711 /* Future possbilities */ 2835362 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}.<ref>{{Cite Q|Q115443776}}</ref> After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite Q|Q118139086}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name=":19">Cañas, Alberto J., et al. "CmapTools: A knowledge modeling and sharing environment." (2004): 125-135. https://thomaseskridge.com/assets/pdf/Canas-2004.pdf</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite Q|Q134545591}}</ref> allowing to synthetize theoretical statements about relationship between concepts.<ref>{{Cite Q|Q30884964}}</ref> They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name=":19" />, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} qhsqnno74sto0hntalwcaqmicrbnigm 2835363 2835362 2026-10-01T15:53:58Z Amélie E. Pereira 3042711 /* Concept maps */ 2835363 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}.<ref>{{Cite Q|Q115443776}}</ref> After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite Q|Q118139086}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name="Cañasal2004">{{Cite Q|Q141613640}}</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite Q|Q134545591}}</ref> allowing to synthetize theoretical statements about relationship between concepts.<ref>{{Cite Q|Q30884964}}</ref> They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name="Cañasal2004"/>, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite book|url=https://mirror.vcu.edu/pub/mx/doc/mxmang10.pdf|title=Statistical Modeling|last=Neale|first=Michael C.|last2=Boker|first2=Steven M.|last3=Xie|first3=Gary|last4=Maes|first4=Hermine H.|publisher=Richmond, VA: Department of Psychiatry|year=1999|location=Virginia Commonwealth University}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other)<ref>{{Cite Q|Q141609011}}</ref>. === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} m1dtut9rp0i6an7j0uy9gtz032s7tuu 2835486 2835363 2026-10-02T09:45:47Z Amélie E. Pereira 3042711 /* Causal diagrams */ 2835486 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}.<ref>{{Cite Q|Q115443776}}</ref> After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite Q|Q118139086}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name="Cañasal2004">{{Cite Q|Q141613640}}</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite Q|Q134545591}}</ref> allowing to synthetize theoretical statements about relationship between concepts.<ref>{{Cite Q|Q30884964}}</ref> They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name="Cañasal2004"/>, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite Q|Q141622061}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other).<ref>{{Cite Q|Q141609011}}</ref> === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts<ref>{{Cite book|title=The Origin of Concepts|last=Carey|first=Susan|date=2011|publisher=Oxford University Press USA - OSO|isbn=978-0-19-536763-8|series=Oxford Series in Cognitive Development Ser|location=Cary}}</ref>. We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} l6a4kkz0xs0b3mwn6ecc0w9c8vorvuo 2835489 2835486 2026-10-02T09:53:12Z Amélie E. Pereira 3042711 /* Conceptual modelling */ 2835489 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}.<ref>{{Cite Q|Q115443776}}</ref> After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite Q|Q118139086}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name="Cañasal2004">{{Cite Q|Q141613640}}</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite Q|Q134545591}}</ref> allowing to synthetize theoretical statements about relationship between concepts.<ref>{{Cite Q|Q30884964}}</ref> They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name="Cañasal2004"/>, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite Q|Q141622061}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other).<ref>{{Cite Q|Q141609011}}</ref> === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts.{{Cite Q|Q141622252}} We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Citation|vauthors=((Peireira, A. E.))|year=2022|title=Usages et transformations d’un commun numérique : les données généalogiques équines|publisher=Paris 10|url=https://theses.fr/s357002|access-date=25 August 2026}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} l0t9mjphuofqdz9ujotg4uko8fcza9b 2835490 2835489 2026-10-02T10:08:23Z Jeanne Noiraud 1366702 /* Quality assessment */ 2835490 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}.<ref>{{Cite Q|Q115443776}}</ref> After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite Q|Q118139086}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name="Cañasal2004">{{Cite Q|Q141613640}}</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite Q|Q134545591}}</ref> allowing to synthetize theoretical statements about relationship between concepts.<ref>{{Cite Q|Q30884964}}</ref> They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name="Cañasal2004"/>, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite Q|Q141622061}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other).<ref>{{Cite Q|Q141609011}}</ref> === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name=":22" /> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name=":22">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts.{{Cite Q|Q141622252}} We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Cite Q|Q141622289}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} c1y5qnq8hzvu5bq6niqh6ez2ushmymx 2835491 2835490 2026-10-02T10:24:57Z Amélie E. Pereira 3042711 2835491 wikitext text/x-wiki == Acknowledgements == === Contributors === {| class="wikitable" |+ !Name !Affiliation !ORCID !Contribution |- |Adélie Ranville |IAE de Grenoble, CERAG lab (https://ror.org/0509qp208) |https://orcid.org/0000-0002-3993-6135 |Research design, database search, article screening, knowledge modelling, article writing |- |Amélie E. Pereira |Laboratoire DICEN IDF |https://orcid.org/0009-0005-5928-5586 |Meta-data enrichement, article writing |- |Finn Nielsen |Technical University of Denmark |https://orcid.org/0000-0001-6128-3356 |Data visualisation |} Contribution statistics are visible here : https://xtools.wmcloud.org/pageinfo/en.wikiversity.org/Just_sustainability_transitions:_a_living_review == Introduction == Just sustainability transition refers to the process of shifting towards sustainable practices in a way that is equitable and inclusive. It includes dimensions of procedural, recognition, distributive and reparative justice and the concept is related to climate justice, environmental justice and energy justice.<ref>{{Cite Q|Q134545572}}.</ref><ref>{{Cite Q|Q129947262}}.</ref> The study of sustainability transitions in social sciences requires dynamic and adaptive research synthesis methods. Sustainability transitions involve complex, multi-level processes influenced by technological, economic, social, and policy factors.<ref name="Geels2020">{{Cite Q|Q121307039}}.</ref><ref name="GeelsAyoub2023">{{Cite Q|Q134545555}}.</ref><ref name="Sovacoolal2025">{{Cite Q|Q134545611}}.</ref> Given the rapidly evolving nature of sustainability-related research, static literature reviews often become outdated, limiting their usefulness for policymakers, scholars, and practitioners. A living literature review – continuously updated with new findings – ensures that emerging insights, case studies, and theoretical developments are integrated cumulatively into the knowledge base. Developing such review will answer the call for more evidence-based practices in management sciences.<ref>{{Cite Q|Q134545576}}.</ref><ref>{{Cite Q|Q46429136}}.</ref> Our project assesses the potential of Wikidata to build living review workflow on sustainability transition. We address three issues encountered by scientists: information overload, knowledge synthesis and results dissemination. === The problem of academic information overload === Global scientific output is quickly growing<ref>{{Cite Q|Q100712015}}.</ref><ref name="Hansonal2024">{{Cite Q|Q131700697}}.</ref><ref>{{Cite Q|Q141613068}}</ref>, pushed by the “publish or perish” model incentivizing researchers to increase the quantity of research outputs. Researchers are subject to information overload as the number of publications to read is beyond what a human brain can handle, they are expected to produce high-quality research under an increasing time pressure<ref name="Hansonal2024" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge.<ref>{{Cite Q|Q134545560}}.</ref> “Wikifying science” may in this context contribute to facilitating researcher’s work while preserving scientific quality. That is why in this project, we aim to build a searchable academic publication database with enriched meta-data that will allow scholars to navigate the existing publications corpus related to just sustainability transition more easily. === The problem of knowledge synthesis === The volume of academic production is rendering knowledge synthesis difficult. Scholars have thus called for making literature reviews cumulative and updatable.<ref>{{Citation|title=Day 2 {{!}} Arnaud Vaganay: Reproducible Literature Reviews|url=https://www.youtube.com/watch?v=Nspd_1cx9kc|date=2017-10-19|accessdate=2026-06-23|last=Berkeley Initiative for Transparency in the Social Sciences (BITSS)}}</ref><ref>{{Cite Q|Q55121944}}.</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name="Krlev2019">{{Cite Q|Q141608208}}</ref> This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite Q|Q40040379}}.</ref><ref>{{Cite Q|Q134545630}}.</ref><ref name="Spadaroal2022">{{Cite Q|Q141606483}}.</ref>). While such reviews method exist for quantitative research producing standardized results, they are not adapted to synthetize social science studies on sustainability transitions that involve diverse methodologies and various disciplinary perspectives. The goal of the project is to propose a demonstration of a living review method for social science findings on just sustainability transition, relying on the collaborative model and tools of Wikimedia projects notably Wikidata, Wikiversity and Wikipedia. === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === The problem of scientific results dissemination === There is urgent need to disseminate knowledge on impactful topics like sustainability transition while proprietary publication models, disinformation and censorship (e.g. US) is threatening access to free and reliable knowledge. In parallel, social scientists struggle to make their work impactful.<ref>{{Cite Q|Q134545557}}.</ref> Wikipedia is a key knowledge dissemination platform widely used by students.<ref>{{Cite Q|Q118144142}}.</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature.<ref>{{Cite Q|Q42013239}}</ref> and that some scholars cite directly Wikipedia.<ref>{{Cite Q|Q66709114}}.</ref> However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives.<ref>{{Cite Q|Q130493308}}.</ref><ref>{{Cite Q|Q107303605}}.</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name="Wikimania2011survey">{{Cite Q|Q141607620}}.</ref> In addition, expert participation is not immune to the gender gap<ref name="Wikimania2011survey"/>. Because of gender segregation in disciplines<ref>{{Cite Q|Q28265069}}.</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite Q|Q27797938}}.</ref>, notably for social science in which women are more present. Our project proposes to improve expert contribution by making wikimedia projects (notably wikidata) useful tools that can facilitate research work, in addition to a key knowledge dissemination platform that is not country or institution-dependent. We propose to approach Wikimedia projects as a powerful (and free) knowledge management infrastructure that researchers could use. The Wikimedia ecosystem offers solutions that have strong potential to put open science principles into practices, including [[wikipedia:FAIR_data|FAIR]] principles and [[wikipedia:Linked_data#Linked_open_data|linked open data]]. == Toward a living review on just sustainability transition == === Just sustainability transition === Just sustainability transition transition is "a fair and equitable process of moving towards a post-carbon society"<ref name="McCauleyHeffron2018">{{Cite Q|Q129947262}}.</ref>. The concept of just transition originated from global trade unions in the 1980s to promote green jobs creation as a key element of sustainability transitions<ref name="McCauleyHeffron2018"/>. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name="McCauleyHeffron2018"/>. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name="Xinxinal2021">{{Cite Q|Q137209041}}</ref><ref name="Heffron2021">{{Cite Q|Q134545572}}.</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name="McCauleyHeffron2018"/><ref name="Xinxinal2021"/><ref name="Heffron2021"/><ref name="Jenkinsal2016">{{Cite Q|Q137210566}}.</ref>. Developping living reviews seem particularly relevant for the just transition literature: first, modeling knowledge and building graphs allows to take into account the complexity of sustainability transitions which involve multiple levels of analysis<ref name="Geels2020" /><ref name="GeelsAyoub2023" /><ref name="Sovacoolal2025" /> and fragmented results coming from various disciplines<ref name="Droubial2022">{{Cite Q|Q137901182}}.</ref>. Then, making literature reviews "living" would allow researchers to be less subject to information overload through a more systematic accumulation of knowledge. Finally, conducting this review with an open science philosophy aswers the challenge of knowledge dissemination, which is crucial in a context of socio-ecological emergency when decision-makers need to rapidely access reliable information on possible sustainability transition trajectories. === Living reviews === The concept of living systematic reviews is recent (2014), so the definition has been regularly reworked<ref name="Why1">{{Cite Q |Q40040379 }}</ref>. Living systematic reviews complement the older concept of [[literature review]]. Its objective is the same : obtain an accurate overview of the state of scientific knowledge on a subject<ref name="Why1" /><ref name="Aklal2017">{{Cite Q|Q50084143}}</ref><ref name="Simmondsal2021">{{Cite Q|Q141608286}}.</ref>. A traditional review may be obsolete by the time it is published, as new studies have emerged between the submission of the manuscript and its publication<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/>. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Aklal2017"/><ref name="Simmondsal2021"/><ref name="Krlev2019"/>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name="Simmondsal2021"/>, such as just transition. Literature review methods are currently evolving with new technological possibilities. Generative artificial intelligence such as ChatGPT are expected to have a strong influence on literature review activities<ref name="Krleval2025">{{Cite Q|Q141608155}}.</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name="Krleval2025"/>, as IA are useful to extract, filter and classify datas<ref>{{Cite Q|Q141608482}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name="Metzendorfal2025">{{Cite Q|Q134545593}}</ref>. Human validation stays notably necessary<ref>{{Cite Q|Q123252496}}.</ref><ref name="Metzendorfal2025"/>. While AI can appear as a solution for scaling literature reviews, we are in the present project exploring another possible scenario which is to use more crowdsourcing in the literature review process. === Wikimedia projects === Wikipedia is a successfull example of large-scaled crowdsourcing of reliable knowledge synthesis. That is why this project proposes to explore the potential of the Wikimedia ecosystem for conducting living reviews. Since Wikipedia does aim to host original research<ref>{{Cite journal|date=2026-06-21|title=Wikipedia:No original research|url=https://en.wikipedia.org/w/index.php?title=Wikipedia:No_original_research&oldid=1360514388|journal=Wikipedia|language=en}}</ref>, we are working on two sister projects : Wikidata and Wikiversity. As its name suggests (wiki and data), [[wikipedia:Wikidata|Wikidata]] is, like Wikipedia, a collaborative project based on wiki editing technology; however, unlike the online encyclopaedia, it contains data rather than articles. Whilst there is a separate Wikipedia for each language version, there is only one Wikidata, containing items organised using unique identifiers. What matters when organising information in Wikidata is not the words used to define each concept, but the concept itself. Wikidata is a [[Databases|database]], more precisely a knowledge base, "collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation".<ref>{{Cite news|last=Chalabi|first=Mona|date=April 26, 2013|title=Welcome to Wikidata! Now what?|url=https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|access-date=October 2, 2021|archive-date=2 October 2021|archive-url=https://web.archive.org/web/20211002152920/https://www.theguardian.com/news/datablog/2013/apr/26/wikidata-launch|url-status=live}}</ref><ref>{{Cite journal|date=2026-06-21|title=Wikidata|url=https://en.wikipedia.org/w/index.php?title=Wikidata&oldid=1360462340|journal=Wikipedia|language=en}}</ref> "A [[wikidata:Q33002955|knowledge graph]] is a structured representation of knowledge that captures information in a machine-readable format.<ref name="Hoganal2022">{{Cite Q|Q141609055}}.</ref> A knowledge graph consists of a graph or network of interconnected data points, where each data point represents a piece of information or a concept, and the relationships between them are explicitly defined. Knowledge graphs organize and store data in a format that facilitates information retrieval, data analysis, and reasoning."<ref>{{Cite Q|Q130027230}}.</ref> Such graphs have a strong potential to conduct knowledge synthesis.<ref name="Krlev2019"/><ref name="Fotopouloual2022">{{Cite Q|Q117837999}}</ref><ref name="Spadaroal2022"/> They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge.<ref name="Spadaroal2022"/> Wikidata is a unique project, designed from the outset for multilingual use.<ref name="VrandečićKrötzsch2014">{{Cite Q|Q18507561}}.</ref> Structuring the data in the form of RDF triples enables a multilingual understanding of the information, provided that their metadata (the ‘label’ and ‘description’ fields) are also translated.<ref name="VrandečićKrötzsch2014"/><ref>{{Cite Q|Q27044266}}</ref> Each Wikidata element in fact comprises a box linking a label (the common term used to refer to the element in each language) to a descrition. Integration into WD is based on adherence to the five principles of linked open data (available on the web, under a free licence, in RDF format, with a unique, identifiable URL for each item, and linked to other data sources), under a CC0 licence, which places the data in the public domain. The use of a unique identifier is a cornerstone of linked open data.<ref>{{Cite Q|Q115725978}}</ref> Indeed, in order to link two databases or knowledge bases together, it is necessary to use an identifier that is both unique to a record or a concept and common to both databases, so as to enable data sharing. This identifier is generally derived from an authority source. In complement to using Wikidata to model knowledge, we decided to use Wikiversity to report and write our research results. [[wikipedia:Wikiversity|Wikiversity]] is another Wikimedia project hosting pedagogical content, original research, and even a publishing house ([[WikiJournal|WikiJournals]]).<ref>{{Cite journal|date=2026-06-09|title=Wikiversity|url=https://en.wikipedia.org/w/index.php?title=Wikiversity&oldid=1358552930|journal=Wikipedia|language=en}}</ref><ref>{{Cite Q|Q100300896}}.</ref> Like all Wikimedia projects, Wikiversity is editable by everyone, have a discussion tab and an history log tab. === Use of Wikidata and Wikiversity for research === A review specifically focusing on the uses of Wikidata in digital humanities projects was carried out by Fudie Zhao in 2022.<ref name="Zhao2022">{{Cite Q|Q116369826}}.</ref> It concluded that WD is used as a content provider, a platform and a technology stack. More specifically, these uses include the implementation of data annotation and enrichment, metadata curation, knowledge modelling and named entity recognition.<ref name="Zhao2022"/> Applications in the life sciences were analysed by Waagmeester et al. in 2019, who highlighted its alignment with the FAIR principles as one of its key strengths for this purpose<ref name="Waagmeesteral2020">{{Cite Q|Q87830400}}</ref>. In this field, WD has been enriched with content from authoritative public sources on genes, proteins and chemical compounds. WD is also used in the social sciences and in artificial intelligence research.<ref>{{Cite Q|Q118130164}}</ref> Wikidata is used as a crowdsourced curation of biomedical ontologies. These ontologies are essential for structuring biomedical knowledge, but their maintenance requires substantial ongoing effort, including updating content and mapping terms to other ontologies and vocabularies. Community curation can distribute this work among many contributors, although it may also introduce errors and inconsistencies. The study investigated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO), combining community contributions with expert review. Disease data from DO were initially added to Wikidata in 2015, and from 2018 onward, Wikidata was compared monthly with the latest DO release. Beyond identifier mappings, Wikidata users proposed structural changes to the ontology, such as new disease terms and modifications to subclass relationships. These suggestions were less often incorporated directly, but frequently prompted expert review and refinement. The authors conclude that this hybrid crowdsourcing model can be applied to other resources synchronized with Wikidata, allowing distributed contributions while retaining expert control over the final curation. Wikidata also increases the visibility and accessibility of biomedical ontologies by connecting them with a broader community of users, tools, and services.<ref name="Waagmeesteral2020"/> Wikidata was relevant because it provides a collaborative platform for aggregating and integrating biomedical knowledge from a large community of contributors. The Human Disease Ontology (DO), meanwhile, provides a structured representation of disease concepts and their relationships. Combining the two made it possible to distribute part of the curation work among Wikidata users while retaining expert control over the quality of the ontology. The researchers used the Disease Ontology as a full ontology, rather than simply as a vocabulary list. The ontology contains disease concepts as well as relationships between them, such as subclass relationships, and mappings to external vocabularies and resources. Wikidata was used as a crowdsourcing and knowledge-integration platform. Contributors could add identifier mappings to resources such as GARD, MeSH, ORDO, and OMIM, as well as propose changes to the ontology structure and new disease terms. These contributions were then reviewed by expert curators before being incorporated into the official Disease Ontology. The researchers seeded Wikidata with disease items from the Disease Ontology and then developed a system to monitor, filter, and prioritize changes made by Wikidata contributors. From 2018 onward, they compared Wikidata with the latest official Disease Ontology release on a monthly basis. The community contributed new mappings and structural suggestions, while expert DO curators manually reviewed and validated these contributions. Most identifier mappings were accepted after review, whereas more complex structural changes were generally examined and refined by experts before being incorporated into the ontology. Thus, the ontology was developed through a hybrid process combining distributed community curation with expert validation.<ref name="Waagmeesteral2020"/> / Short version / Waagmeester et al. (2020)<ref name="Waagmeesteral2020"/> evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review.<ref name="Waagmeesteral2020"/> Wikidata was seeded with DO disease items starting in late 2015, and from 2018 onward the disease data were compared monthly with the most recent DO release. In the first comparison, Wikidata users had added 2,030 cross-references to GARD and MeSH, mainly through a small number of contributors using an identifier-mapping interface. After manual review by DO curators, 2,007 (98.9%) were judged correct and included in the next DO release. Subsequent monthly reports, which also included ORDO and OMIM mappings, showed approval rates above 90%. Contributors also proposed structural changes, such as new disease terms and revised subclass relationships. These were rarely adopted without modification, but they often prompted further review and refinement by DO curators. The authors argue that this approach can be generalized to any resource synchronized with Wikidata, allowing distributed contributions while preserving expert control over the final curation. They also note that integration into Wikidata increases the resource's visibility by engaging a broader community of users, curators, tools, and services. === Knowledge graphs for research === The theory database of behaviour change (https://theory-database.hbcptools.org/) references more than 70 theories of behaviour change and uses an ontology-based modelling system (OBMS) to represent constructs and their relationships in a formalized way.<ref name="Westal2019">{{Cite Q|Q92955740}}.</ref><ref name="Haleal2020">{{Cite Q|Q102211870}}.</ref> Behaviour-change theories are written in natural language, sometimes with ad hoc diagrams. This makes them ambiguous: the same construct gets different labels, and the same label is used for different constructs, even within one theory. The authors argue this hinders comparing, integrating and applying theories, and may explain why interventions are often disconnected from explicit theory. A review of 83 theories showed these problems. Existing resources did not solve this. The Grid-Enabled Measures database, the Science of Behaviour Change repository and the Theoretical Domains Framework organise or synthesise constructs, but none standardises how theories are represented. A formal system of defined constructs and typed relationships, of the kind used to build ontologies, was chosen to make theories precise and comparable. It would also allow computational searching, clustering and reasoning across theories. It is closer to a full ontology than to a vocabulary list, though the authors do not claim a finished ontology. The system has three parts: * Defined constructs. Each has a label and a definition (85 constructs across the five theories). * Typed binary relationships. Each theory is written as "subject–relationship–object" propositions. The relationships fall into three types: causal (e.g. "is influenced (+) by", "may be influenced by", "correlates with"), semantic ("type of", "value of", "has attribute") and structural ("part of", "has start", "has end"). * Diagrams. Propositions are also shown graphically, and the diagrams can be exported as subject–relationship–object triples. The authors say such representations "can be used to create formal 'ontologies'". They note, though, that the system is not yet formally linked to OWL, which would allow greater expressivity and automated inference. They plan to do this in the next phase. They selected five theories from the 83 in Davis et al.: the Health Belief Model, the Information-Motivation-Behavioural Skills model, Social Cognitive Theory, the Theory of Planned Behaviour and the Transtheoretical Model. These were chosen as the most frequently used in behaviour-change interventions. Construct labels were taken from the original published descriptions. Definitions were drafted from the theory text and reviewed by two additional authors. Where the theory text gave no definition, they consulted the APA dictionary, then other dictionaries and sources. Failing that, they wrote definitions from the theory text and dictionary definitions of the label's words. The relationship library was built incrementally, adding types only as needed to capture the theories. Two researchers independently coded each theory into triples, then reached an agreed version through team discussion. The construct definitions and theory representations were sent to the theory authors or, where authors couldn't be reached, to experts. The experts were found by searching Web of Science and Scopus for the most frequent citers of each theory. Proposed changes were included, or the authors explained why not. Validation was qualitative. There was no quantitative measure such as inter-rater agreement. The authors report that the theory authors "appeared to be satisfied" that the system captured their theories, but they gave no formal test. The reviews also exposed issues. The Theory of Planned Behaviour author did not think the "behavioural belief" construct was needed, but the authors kept it because the logic requires it. The Transtheoretical Model author noted that the representation omits transitions back to earlier stages, which the system could in principle handle. Limits : Only five theories were covered. No formal link to OWL yet. The representations capture only the main parts of each theory, and the diagrams become hard to read as propositions are added. . Why was an ontology-based approach relevant? Natural language is a poor medium for theories. Behaviour-change theories are expressed in natural language, which the authors say is ambiguous and limits comparison, integration and testing. Overlapping scope, vague definitions and inconsistent construct labels make it hard to choose or combine theories. Theories need to be computable. To search, compare, test and integrate theories efficiently, they must be specified in a way that is "clear, consistent and computable". Ontology-style construct–relationship–construct triples make theories computer-readable and searchable, and give a basis for logical inference. No existing ontology covered this domain. A scoping review found 15 ontologies related to human behaviour change, none of which represented its breadth and detail. This motivated the project's own Behaviour Change Intervention Ontology (BCIO), which the authors plan to link the theories to. 2. Vocabulary list or full ontology? Neither exactly. The authors state that the OBMS "is not an ontology", because ontologies typically represent knowledge about the world rather than theories about it. It does use the same modelling approach that ontologies use. What it is. It is a formal system of labelled constructs plus typed relationships, written as triples such as "intention–influences–behaviour". Diagrams are drawn in LucidChart and exported as CSV, and Python scripts extract the triples into a searchable database (Flask web interface, Whoosh search). Relationship types. 14 were used across the 76 theories. The most common were "influences" (995 triples) and "part of" (578), followed by "type of", multiplicative and positive influences, and others. More than a vocabulary list. It goes beyond a flat list of terms because it encodes relationships between constructs, including causal, semantic (type of), structural (part of) and process ("transitions to") types. Moderators are handled by "reification", treating a relationship as a construct. Not yet fully ontological. Constructs are identified by their labels only. There are no definitions or formal semantics yet, and this is the main gap. The authors plan to annotate constructs with entities from the BCIO, which would add synonyms, definitions and formal logic (e.g. OWL) to check consistency. The only formal ontology named in the paper is the BCIO, and it is a planned future link rather than something used here. 3. How was it developed and validated? Development Selection. 83 theories were screened from Davis et al. (2015). 71 new ones were represented, and combined with the five from West et al. (2019) they give 76. Seven were excluded: two did not link any construct to behaviour, one lacked a behaviour construct, and four had been integrated into the Theory of Triadic Influence. Constructs. At least two researchers independently extracted constructs from the original sources. Disagreements were settled by discussion, or by the study leads (SM and RW) if needed. The extraction was then cross-checked against the theory summaries in Michie et al. (2014). Diagrams. One researcher drafted each diagram, and a second or third refined it. There were 19 conceivable relationship types at the start, revised for parsimony. Only one type ("transitions to") was added to those in West et al. (2019). Validation Author and expert review. Each diagram went to the theory author or an expert. If none of the 15 authors could be reached (14 deceased, 1 retired), an expert was found through Web of Science and Scopus. Of the 69 contacted, 50 (72.5%) responded and 38 gave feedback. Iterative revision. A researcher identified changes and a second reviewed them, with revisions repeated until agreement. A non-response after two reminders counted as approval. Outcome. 35 theories (49%) were finalised with no or very minor changes. The other 36 (51%) changed constructs (7), relationships (15) or both (14). Openness. Data, diagrams and code are on OSF, and the database is online. Limitations and reviewer concerns Non-response counted as approval, and validation was qualitative with no agreement statistics. Only about 20% of construct names appeared in more than one theory. Both reviewers suspect this understates conceptual overlap, because constructs were matched by label rather than definition. Reification makes triples nested and complex, and the reviewers question how well moderators are represented. The reviewers also asked how the system handles non-deliberative, environmental (behaviourist) models and socio-cultural influences. Persons in Context (PiCo) is a knowledge model allowing to link the reconstruction of historical persons to observations and sources<ref>{{Cite Q|Q141609117}}</ref>. == Research question and hypothesis == Our research question is : '''How can Wikimedia projects contribute to building a collaborative living review on just sustainability transition ?''' In this project, we aim to test 4 hypothesis : ● '''Hypothesis 1:''' Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations. ● '''Hypothesis 2:''' Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (e.g. conceptual typologies, cause-effect chains…). ● '''Hypothesis 3:''' SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs. ● '''Hypothesis 4''': Wikimedia or Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links (following the ideal of linked open data). We also have 2 assumptions : ● '''Assumption 1:''' Wikimedia projects have to be integrated into validated scientific protocols in order to be a valuable research tool. ● '''Assumption 2:''' Wikimedia project contribution has to be made interoperable with tools, methods and data types already used by researchers. == Methodology == Our study rely on a meta-review, that is a review of existing literature reviews. Data presented in literature reviews are usually presented as tables or diagrams, and sometimes provided as supplementary materials in publications. However, these data are not made interoperable and are not used to update prior literature reviews. Our goal was to synthesize results of previous literature reviews by making their findings compatible with linked open data and open science standards using Wikidata, Wikiversity, and other open-science infrastructures. The first step was to build and enrich the bibliographic metadata of a corpus of articles we selected into Wikidata. The second step was to model the content of these articles in Wikidata (e.g. typologies, causes-effects relationships...). The third step was to experiment relevant visualization of this content (e.g. causes-effects graphs). The las step was to write our report on a Wikiversity page, including links to our knowledge graph, following a linked open data philosophy. == 1. Building an academic corpus and enriching bibliographic metadata == The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations). To do so we imported academic references into Wikidata, and explored the advantages of constituting a scholarly corpus on Wikidata in comparison (or in complementarity) to existing tools used by researchers such as reference management softwares and knowledge management softwares. Reference management software (Zenodo, Mendeley…) are used to collect scientific item metadata and integrate them into academic writing. They can also be used to analyze and annotate academic articles and can include export functions making the data interoperable with other analysis tools. Knowledge management software (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…) are used by some researchers to organize their ideas. To build and enrich our academic corpus on Wikidata, we searched existing databases, selected the sample of articles we wanted to study, imported these articles metadata into Wikidata, enriched these metadata and finally reflected on the advantages and limitations of Wikidata to build a rich academic corpus. === Database search === Doing a systematic review on all aspects of just transition would have resulted in too many articles to review. We thus decided to first explore one aspect of justice : procedural justice. Procedural justice is about the fairness of decision-making processes related to transitions<ref name="Jenkinsal2016"/> such as the inclusion of those impacted by these decisions<ref name=":5">{{Cite Q|Q137210229}}</ref> (e.g. the participation of affected communities in decisions related to the construction of new infrastructures<ref name="McCauleyHeffron2018"/>). Procedural justice can include issues of community and citizen participation in decision making, their political representation, their consultation, or the integration of their knowledge, with a focus on neglected population (indigenous people, women, gender and ethnic minorities)<ref>{{Cite Q|Q137210566}}</ref>. For our search, we selected keywords related to procedural justice (procedural justice OR procedural fairness OR democracy OR participation OR participatory) and keywords related to sustainability transition (sustainability OR energy OR climate) AND (transition OR transitions). We conducted preliminary searches in various databases including Web of science, Go Triple, Dimensions and OpenAlex. Web of Science was the database offering the most relevant restults and included the possibility to filter results to display only litterature reviews. Articles metadata were exported (in .ris format) and then imported into the reference manager software Zotero. {| class="wikitable" |+ !Keywords search !Database !Search date !Filters !Number of results |- |(((TS=(procedural justice OR procedural fairness OR democracy OR participation OR participatory)) AND TS=(sustainability OR energy OR climate)) AND TS=(transition OR transitions)) AND TS=(review OR reviews) |Web of Science (all databases, all dates) |December 2025 |Document type: Review Article |362 |} === Article selection === Articles abstract were then screened and we selected only articles which were litterature reviews focusing on concepts related to procedural justice as their main topics. We excluded article which were : * Not related to sustainability transition (e.g. sustainable shift in..., hard science papers...) * Not literature reviews (e.g. review of policies/initiatives/cases, review notes, book review...) * Not related to procedural justice but to participation into markets, participation in eco-friendly behaviors * Including justice consideration only in “future research” suggestions * Discussing participatory research methodologies (e.g. participatory modelling) without approaching it as an issue of justice, power or democracy * Discussing procedural justice concepts as key variables or key results without it being the main focus of the paper The files with the lists of included and excluded articles are available on the archive plateform Zenodo : https://zenodo.org/records/20749974 === Importing selected articles into Wikidata === Before importing the selected articles meta-data into Wikidata, we first ran [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 a script] to check if any article was already present in Wikidata. Next, we used [https://gist.github.com/zuphilip/90acdc3eac4109830db1b3ab855fcb24 another script] that checks the ISSN of the publication in Wikidata and add P-Q-pairs in the extra field of Zotero. Then we exported the articles data using the "export to Wikidata QuickStatements" function of Zotero and use the QuickStatements tool to add them to Wikidata. Next we used the [[wikidata:Wikidata:Zotero/Cita|Cita]] (V1.0.0-beta.17) Zotero add-on to add articles QID in Zotero. At this point we identified that duplicates had been created in Wikidata (possibly because the initial [https://gist.github.com/zuphilip/aa9f59271fcb0807fb20c7d0110d26e4 script] did not work that well because of the recent [[wikidata:Wikidata:SPARQL_query_service/WDQS_graph_split|Graph Split]] on Wikidata). We merged duplicates on wikidata using the [[wikidata:Help:Merge|"Merge" gadget]] on Wikidata. We checked manually for duplicated statments in those items. === Article classification through metadata enrichement === Metadatas are data describing other data. The metadata of academic items usually include title, author, publication outlet, publication date, pages, DOI, URL... and can be structured following specific standards (e.g. [[wikipedia:Dublin_Core|Dublin Core]]). In academic databases such as WOS or OpenAlex, the only metadata available regarding the content of an academic article are the abstract and sometimes keywords. However, researchers conducting literature reviews need more precise informations. An important part of literature review work can thus be about describing what the articles are about. For example, describing industry focus, academic discipline, geography of research sites (countries), stakeholder focus (community, consumer, worker...), type of study (case study, theory development) or methodology (quantitative, qualitative, mixt) (e.g. <ref name=":5" />). By metadata enrichment, we mean completing metadata to include additional information about the content of an academic piece. In Wikidata, each type of information is added using a specific property. A property is the edge that links two entities in the Wikidata knowledge graph. We selected three Wikidata properties to describe the content of our selected articles : {{Wikidata entity link|P921}} to describe what the article is about, {{Wikidata entity link|P8363}} to describe its main methodology/research design and {{Wikidata entity link|P6153}} to describe the geographical scope of the study. We also worked on adding {{Wikidata entity link|P50}}. ==== Adding {{Wikidata entity link|P921}} ==== We first read the articles abstracts and listed relevant topics and their Wikidata ID in a shared spreadsheet. These topics were : {| class="wikitable" |+ !Qid !Main topic !Description |- |[[d:Q42377797|Q42377797]] |acceptability |characteristic of a thing being subject to acceptance for some purpose |- |[[d:Q2798912|Q2798912]] |accountability |concept of responsibility in ethics, governance and decision-making |- |[[d:Q421953|Q421953]] |actor–network theory |theory within social science |- |[[d:Q84459973|Q84459973]] |affordability | |- |[[d:Q185836|Q185836]] |age of a person |time elapsed since a person was born |- |[[d:Q4764988|Q4764988]] |animal studies |field in which animals are studied in a variety of cross-disciplinary ways |- |[[d:Q4338318|Q4338318]] |awareness |state or ability to perceive, to feel, or to be conscious of events, objects, or sensory patterns |- |[[d:Q4930066|Q4930066]] |blue carbon |carbon captured by the world's coastal ocean ecosystems |- |[[d:Q430460|Q430460]] |capability approach |economic theory |- |[[d:Q7569|Q7569]] |child |human between birth and puberty |- |[[d:Q4116870|Q4116870]] |civic engagement |individual or group activity addressing issues of public concern |- |[[d:Q125928|Q125928]] |climate change |human-caused changes to climate on Earth |- |[[d:Q260607|Q260607]] |climate change adaptation |process of adjustment to actual or expected climate change and its effects, seeking to moderate or avoid harm or exploit beneficial opportunities |- |[[d:Q1291678|Q1291678]] |climate justice |term linking the climate crisis with environmental and social justice |- |[[d:Q2270945|Q2270945]] |co-creation |product or service design process in which input from consumers plays a central role |- |[[d:Q16972712|Q16972712]] |co-design |approach to design attempting to actively involve all stakeholders |- |[[d:Q16324410|Q16324410]] |coproduction |product or service design process in which input from consumers plays a central role |- |[[d:Q11024|Q11024]] |communication |act of conveying intended meaning |- |[[d:Q177634|Q177634]] |community |social unit of human organisms who share common values |- |[[d:Q5154673|Q5154673]] |community choice aggregation |alternative energy supply system |- |[[d:Q113514984|Q113514984]] |community energy |delivery of community-led renewable energy, energy demand reduction and energy supply projects |- |[[d:Q65807646|Q65807646]] |community participation |The taking part by members of a community in decisionmaking processes related to the development of their community |- |[[d:Q188843|Q188843]] |cosmopolitanism |ideology that all human beings belong to a single community, based on a shared morality |- |[[d:Q11693783|Q11693783]] |decarbonization |change of economy, especially of energy industries, towards lower carbon dioxide emissions |- |[[d:Q284289|Q284289]] |deliberative democracy |form of democracy focusing on consensus |- |[[d:Q7174|Q7174]] |democracy |form of government |- |[[d:Q552284|Q552284]] |distributive justice |concept of the socially just allocation of goods |- |[[d:Q1230584|Q1230584]] |diversity |concept in sociology and political studies |- |[[d:Q1049066|Q1049066]] |ecological economics |research field on the interdependence of human economies and natural ecosystems |- |[[d:Q8134|Q8134]] |economics |social science that studies the production, distribution, and consumption of goods and services |- |[[d:Q868575|Q868575]] |empowerment |providing increased autonomy |- |[[d:Q295865|Q295865]] |ecosystem service |benefits created by nature, forests and environmental systems |- |[[d:Q138359220|Q138359220]] |energy citizenship |involvement of citizens in energy-related decisions |- |[[d:Q16869822|Q16869822]] |energy consumption |amount of energy or power used |- |[[d:Q1358789|Q1358789]] |senior |elderly person |- |[[d:Q14944319|Q14944319]] |energy democracy |concept in environmental justice movement |- |[[d:Q192704|Q192704]] |energy efficiency |ratio between the useful energy output and the input of a machine |- |[[d:Q24965464|Q24965464]] |energy modeling |process of building computer models of energy systems in order to analyze them |- |[[d:Q1805337|Q1805337]] |energy policy |policy addressing energy issues |- |[[d:Q1341244|Q1341244]] |energy poverty |lack of access to modern energy services |- |[[d:Q3406659|Q3406659]] |energy production |conversion of energy from a primary source into a form useful to humans |- |[[d:Q117091181|Q117091181]] |energy justice |subconcept of economic equality |- |[[d:Q3456219|Q3456219]] |energy renovation |building works aimed at reducing energy consumption and decarbonising the energy sources used |- |[[d:Q2700433|Q2700433]] |energy security |national security considerations of energy availability |- |[[d:Q837718|Q837718]] |energy storage |capture of energy produced at one time for use at a later time |- |[[d:Q795757|Q795757]] |energy transition |long-term structural change towards sustainable energy systems |- |[[d:Q1479527|Q1479527]] |environmental justice |system of fairness |- |[[d:Q771773|Q771773]] |fairness |concept in sociology and generally the interaction of society |- |[[d:Q56395513|Q56395513]] |farming system |method of agricultural production defined by its physical practices and economic characteristics |- |[[d:Q5465532|Q5465532]] |food system |all processes and infrastructure involved in feeding a population |- |[[d:Q4421|Q4421]] |forest |dense collection of trees covering a relatively large area |- |[[d:Q48277|Q48277]] |gender |social concept which distinguish the different gender categories |- |[[d:Q1553864|Q1553864]] |governance |all of the processes of governing, whether undertaken by a government, market or network, whether over a family, tribe, formal or informal organization or territory and whether through the laws, norms, power or language of an organized society |- |[[d:Q8458|Q8458]] |human rights |inalienable fundamental rights to which a person is inherently entitled |- |[[d:Q11376059|Q11376059]] |human rights violation |act or omission which contravene the principles of human rights |- |[[d:Q103817|Q103817]] |indigenous people |first inhabitants of an area and their descendants |- |[[d:Q113561794|Q113561794]] |indigenous science |indigenous knowledge applied to the scientific method |- |[[d:Q770480|Q770480]] |injustice |quality relating to unfairness or undeserved outcomes |- |[[d:Q17142211|Q17142211]] |interactional justice |the perceived appropriateness of interpersonal treatment |- |[[d:Q1516555|Q1516555]] |intersectionnality |theoretical framework of multidimensional oppression |- |[[d:Q6316391|Q6316391]] |just transition |Framework developed by the trade union movement to encompass wide range of social interventions needed to secure decent work opportunities and a greener economy. |- |[[d:Q366139|Q366139]] |legitimation |the process of making something acceptable and normative to a group |- |[[d:Q3027857|Q3027857]] |living lab |user-centered, open innovation ecosystem integrating research and innovation in real life communities |- |[[d:Q59679511|Q59679511]] |low income |home with little money |- |[[d:Q43619|Q43619]] |natural environment |all living and non-living things occurring naturally on Earth or some region thereof |- |[[d:Q127514833|Q127514833]] |nature-positive |global goal to halt and reverse nature loss by 2030 |- |[[d:Q13023682|Q13023682]] |non-human |organism not in the genus Homo |- |[[d:Q728646|Q728646]] |partnership |arrangement in which parties agree to cooperate to advance their mutual interests |- |[[d:Q3907287|Q3907287]] |policy making |the act of developing policy |- |[[d:Q9357091|Q9357091]] |political theory |class of theory |- |[[d:Q265425|Q265425]] |postcolonialism |academic discipline |- |[[d:Q25107|Q25107]] |power |ability to influence the behavior of others |- |[[d:Q442100|Q442100]] |procedural justice |fairness in the processes that resolve disputes and allocate resources |- |[[d:Q7249406|Q7249406]] |project governance |management framework |- |[[d:Q7257735|Q7257735]] |public engagement |Policy-making practice |- |[[d:Q541936|Q541936]] |public participation |participation of citizens in various policy decisions and planning processes |- |[[d:Q6142016|Q6142016]] |recognition justice |social philosophy theory |- |[[d:Q10509953|Q10509953]] |renewable electricity |electricity from renweable sources |- |[[d:Q12705|Q12705]] |renewable energy |energy collected from renewable resources |- |[[d:Q56510941|Q56510941]] |renewable energy policy | |- |[[d:Q1165392|Q1165392]] |restorative justice |approach to justice where victims and perpetrators mediate a restitution agreement |- |[[d:Q4414036|Q4414036]] |rural population |inhabitants of rural areas or of small towns classified as rural |- |[[d:Q17152351|Q17152351]] |smart system |adaptive intelligent systems |- |[[d:Q187588|Q187588]] |social class |group of people categorized in a hierarchy based on socioeconomic factors |- |[[d:Q264892|Q264892]] |social justice |concept that discrimination recognized in society should be remedied |- |[[d:Q34749|Q34749]] |social science |academic disciplines concerned with society and the relationships between individuals in society |- |[[d:Q2930198|Q2930198]] |stakeholder participation |involvement of groups or individuals affected by the actions of an entity |- |[[d:Q125359881|Q125359881]] |sustainability transition | |- |[[d:Q219416|Q219416]] |sustainability |ability of human civilization to coexist with the biosphere in a steady state |- |[[d:Q131201|Q131201]] |sustainable development |mode of human development that meets current demands without compromising the needs of future generations |- |[[d:Q7649586|Q7649586]] |Sustainable Development Goals |set of United Nations-defined global development goals and climate change |- |[[d:Q69883|Q69883]] |urban planning |technical and political process concerned with the use of land and design of the urban environment |- |[[d:Q920600|Q920600]] |urban renewal |program of land redevelopment in cities, often where there is urban decay |- |[[d:Q3376054|Q3376054]] |vulnerable population |group of persons whose range of options is severely limited, are subjected to coercion, or who may be compromised in their ability to give informed consent |- |[[d:Q107389921|Q107389921]] |water-management | |- |[[d:Q7981051|Q7981051]] |well-being |measure of how well life is to someone or a group with factors such as health, happiness and satisfaction |- |[[d:Q467|Q467]] |woman |female adult human |- |[[d:Q188867|Q188867]] |future studies |study of possible, probable, and preferable social, technological and political futures |- |[[d:Q1038171|Q1038171]] |participatory design |active involvement of all stakeholders in the design process |}Then, for each article, we inferred what the {{Wikidata entity link|P921}} was from the abstracts and author provided keywords. ==== Adding {{Wikidata entity link|P8363}} ==== The sample of article we selected included only litterature reviews, but we wanted to describ what kind of literature review it was. We first read abstracts to identify all the different types of litterature reviews present in the corpus and created wikidata items which did not exist, for example {{Wikidata entity link|Q137209848}} and {{Wikidata entity link|Q137174203}}. We improved some of these method items using the methodological references cited in the reviewed papers. For example, we added a statement saying that {{Wikidata entity link|Q101116078}} can have {{Wikidata entity link|Q653137}} as {{Wikidata entity link|P13391}}.<ref>{{Cite Q|Q115443776}}</ref> After this step, the {{Wikidata entity link|P279}} of {{Wikidata entity link|Q2412849}} in Wikidata were : {| class="wikitable" |+ !Qid !Study type !Description |- |[[d:Q603441|Q603441]] |bibliometrics |statistical analysis of written publications, such as books or articles |- |[[d:Q472342|Q472342]] |scientometrics |study of measuring and analysing science, technology and innovation |- |[[d:Q815382|Q815382]] |meta-analysis |statistical method that summarizes data from multiple sources |- |[[d:Q1504425|Q1504425]] |systematic review |publication type, study that gathers, analyzes, and communicates the results of research and information on a topic |- |[[d:Q2412849|Q2412849]] |literature review |process of information search and text of a review article (Q7318358), which includes the current knowledge including substantive findings, as well as theoretical and methodological contributions to a particular topic |- |[[d:Q6822263|Q6822263]] |meta-regression |statistical tool used in meta-analyses |- |[[d:Q7301211|Q7301211]] |realist evaluation |theory-driven evaluation used in evaluating social programmes |- |[[d:Q17007303|Q17007303]] |combinatorial meta-analysis |study of the statistical properties of combinations of studies from a meta-analytic dataset |- |[[d:Q70470634|Q70470634]] |network meta-analysis |meta-analysis of randomized trials in which estimates of comparative treatment effects are visualized and interpreted from a network of interventions |- |[[d:Q101116078|Q101116078]] |scoping review |search for concepts by mapping the language and data which surrounds those concepts and adjusting the search method iteratively to synthesize evidence and assess the scope of an area of inquiry |- |[[d:Q110665014|Q110665014]] |narrative review |type of literature review, without structured method of retrieval and analysis |- |[[d:Q137174203|Q137174203]] |conceptual review |academic research aiming to review existing concepts and definitions in the litterature |- |[[d:Q137174450|Q137174450]] |critical review |type of literature review analysing strenghts, major contributions, mistakes and neglected issues in an academic field of research |- |[[d:Q137209848|Q137209848]] |integrative literature review |type of literature review |- |[[d:Q110665014|Q137211242]] |narrative review |type of literature review, without structured method of retrieval and analysis |}For each article, we added the {{Wikidata entity link|P8363}} based on the abstract and method sections. In case of doubt, we compared our interpretation. ==== Adding {{Wikidata entity link|P6153}} ==== When an article had a specific geographical focus, we used the property {{Wikidata entity link|P6153}} to describe it. For example, the article "{{Wikidata entity link|Q137901202}}" focused on {{Wikidata entity link|Q132959}}. ==== Adding {{Wikidata entity link|P50}} ==== When scholarly metadata are imported into Wikidata, the name of authors are stored as a chain of characters and linked to the property {{Wikidata entity link|P2093}}. The property {{Wikidata entity link|P50}} allows to make a link with a Wikidata item representing the author. This avoids the problem of homonym authors by linking a unique identifyer to authors in Wikidata and linking this identifier to existing ones such as ORCID. We used the [https://author-disambiguator.toolforge.org/ Author Disambiguator] tool to create Wikidata items for researchers who did not yet have one. This tool helps to minimise errors caused by homonyms among researchers by categorizing scientific publications into thematic groups. It also automatically searches for [[d:Wikidata:ORCIDator|ORCID]], ResearchGate and VIAF pages. ==== Adding {{Wikidata entity link|P6977}} ==== We explored the possibility to model review networks, that is linking review paper to reviewed papers (and not broadly cited papers). We selected one of the paper which had the most detailed list of reviewed papers ({{Wikidata entity link|Q114306483}}), then we added this list in Wikidata using Open refine. Then we snowballed this process for the reviewed papers which were also litterature reviews. === Advantages and limitations of Wikidata to build a rich living academic corpus === To share the result of our work, we exported the dataset we build on Wikidata and shared it on the open archive Zenodo : https://doi.org/10.5281/zenodo.20749973. The data is also available directly in Wikidata. The goal of this step was to test '''Hypothesis 1''' (Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations)'''.''' The sections below discuss the advantages and limitations of wikidata regarding this hypothesis. ==== Advantages of Wikidata ==== Key advantages of Wikidata are its flexible and collaborative nature as well as its interoperability. Wikidata ontology (that is how the data are structured) is collaboratively defined and properties can be added if relevant (after validation by the community). Compared to global databases like WOS or OpenAlex, Wikidata allows anyone to enter more metadata about each academic articles. Another notable advantage is that Wikidata items can be used as an interoperable [[wikipedia:Controlled_vocabulary|controlled vocabulary]]. For example, when we stated that the {{Wikidata entity link|P921}} of the article {{Wikidata entity link|Q114306483}} was {{Wikidata entity link|Q795757}}, "energy transition" was not just a word but a concept with its unique identifyer, linked to identifiers in other databases such as the Google Knowledge Graph ID or BNCF Thesaurus ID. Wikidata's collaborative nature is here adain an advantage. Contrary to institutional thesaurus, Wikidata allows anyone to add new concepts. This is particularly interesting as existing controlled vocabularies rarely reflect the degree of precision that researchers need in their work. The multilingual nature of Wikidata was also a strengh, some Wikidata contributors added labels for the concepts we used into different languages (For example, contributors added labels for {{Wikidata entity link|Q14944319}} in Armenian and Slovenian, languages we do not speak at all). ==== Limitations of Wikidata ==== The limitations of Wikidata is that it is not yet well integrated with the tools researchers use to do literature reviews (kowledge management softwares and bibliographic databases). Compared to reference management softwares (Zenodo, Mendeley…) and knowledge management softwares (Obsidian, Zettlr, Room Research, Notion, Logseq, Reflect…), Wikidata is too general and does not allow to work on full texts. References and knowledge management softwares allow researcher to build their own specialised knowledge base, by taking notes and highlighting the content of the full texts. Wikidata is not connected to this process and there is a missing tool to facilitate the construction of graphs from the qualitative analysis of texts. In addition, when one is working on a specific corpus of item in Wikidata, it is also difficult to keep track of this corpus. We linked each academic item we were working on to our research project by adding a statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}, but it was still relatively difficult to "filter" the part of the knowledge graph we were working on. Compared to bilbiographic catalogues (OpenAlex, Web Of Science, GoTriple...), Wikidata will never be as exhaustive and do not offer user-friendly search functions. Since 2014, an important amount of bibliographic data was imported in Wikidata with the project [[d:Wikidata:WikiCite|Wikicite]]. At the time of its creation, Wikicite was adressing the issue of closed bibliographic data and was trying to make these data open, many academic items were imported automatically in Wikidata through scraping. This practice was abandoned because the large amont of bibliographic data congested queries on Wikidata (this led to the decision to split the Wikidata graph between academic and non academic entities), and because new open science initiatives, notably OpenAlex (2022), are now taking on the task of creating a exhaustive catalogues of all scholarly production. In this context, the community has to rethink the purpose of Wikidata regarding bilbiographic data. ==== Future possbilities ==== A solution to the limitations would be to developp the role of Wikidata as a link between other tools of the open science ecosystem. For example, developping and maintaining plugins or extensions for specialised softwares like Zotero, Wikibase, and Omeka could connect Wikidata with more specialised graphs. Such extensions could help building local graphs by allowing the reuse of wikidata item (eg. autocompletion), but also help contributing to Wikidata thanks to export features. (Example :<ref>{{Cite Q|Q118139086}}</ref>) Wikidata could then be an intermediary between locally curated corpus and more exhaustive bilbiographic catalogues such as OpenAlex. For example, Wikidata items could be used to tag articles in a more precise way instead of using keywords and sharing enriched corpus in Wikidata could help to train more precise taging algorythms. == 2.Modelling the content of litterature reviews == The goal of this step was to test '''Hypothesis 2''' (Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference) by modelling the content of our selected articles into Wikidata. [[wikipedia:Knowledge_modeling|Knowledge modelling]] is the process of making a machine readable model of knowledge. As we have a background in social sciences, we felt the need to question the relationship between this process and other methodologies such as concept mapping, thematic networks and causal networks. We present these methodologies before describing our current knowledge modelling experimentations. === Concept mapping, thematic networks and causal networks === This section presents social science methodology that presents similarities with knowledge modelling. ==== Concept maps ==== [[File:Conceptual_Diagram_-_Example.svg|link=https://en.wikipedia.org/wiki/File:Conceptual_Diagram_-_Example.svg|thumb|Example conceptual diagram|251x251px]]Concept maps are ''concepts'' (boxes) and ''propositions'' (arrow indicating the relationship between two boxes)<ref name="Cañasal2004">{{Cite Q|Q141613640}}</ref>. Concept maps can be a powerful literature review tool<ref>{{Cite Q|Q134545591}}</ref> allowing to synthetize theoretical statements about relationship between concepts.<ref>{{Cite Q|Q30884964}}</ref> They can be built using specialised softwares (e.g. [https://cmap.ihmc.us/ Cmap]<ref name="Cañasal2004"/>, Altas.Ti "network" feature...). The "box and arrow" logic is similar to how knowledge is modelled on Wikidata : the equivalent of concepts is ''item'' and the equivalent of propositions are ''statements''. The difference between a softwares like Cmap and Wikidata is the underlying format of the data. ==== Thematic networks ==== [[File:Thematic network example.jpg|thumb|447x447px|Structure of a thematic network (Source: based on Attride-Stirling 2001)]] A thematic network is “simply a way of organizing a thematic analysis of qualitative data”<ref name="Attride-Stirling2001">{{Cite Q|Q134545550}}</ref>. It is compatible with classical coding strategies such as [[grounded theory]]<ref>{{Cite Q|Q140050249}}</ref>. Thematic networks can be used to visualise the data structure after identifying themes and help structure and interpret the data<ref name="Attride-Stirling2001"/>. The principle is to assemble basic themes into more general themes. Qualitative researchers usually use {{Wikidata entity link|Q4550939}} and qualitative coding to identify themes and sub-themes. However, the nature of the relationship between these various themes and sub-themes is often not specified. [[File:Adoption_CLD.svg|link=https://en.wikipedia.org/wiki/File:Adoption_CLD.svg|thumb|421x421px|Causal loop diagram of ''Adoption'' model, used to demonstrate systems dynamics]] ==== Causal diagrams ==== The use of diagrams to represent causal relationship exist in various research practices. In statistics, researchers sometime present models with boxes and arrows representing correlations and/or causations<ref>{{Cite Q|Q141622061}}</ref>. In qualitative research, building grounded theory models is about "[accounting] for not only all the major emergent concepts, themes, and dimensions, but also for their dynamic interrelationships. Speaking in classic boxes-and-arrows terms, this process amounts to assembling the constellation of boxes with a special focus on the arrows."<ref name="Gioiaal2013">{{Cite Q|Q141609039}}</ref> After identifying themes, qualitative researchers are expected to theorize the "arrows" between themes<ref name="Gioiaal2013"/> Researchers relying on system theory also use causal loop diagram where boxes represent variables and arrows represent causal influence (positive or negative), causal relationship can "feedback" (two variables can influence each other).<ref>{{Cite Q|Q141609011}}</ref> === Knowledge modelling in Wikidata : first round of analysis === This section presents our knowledge modelling experimentation in Wikidata. ==== Conceptual modelling ==== Our first step was to reflect on what is a "concept" and what kind of wikidata properties could be used to model concepts in Wikidata. Scholars in management have called for more rigorous ways to define concepts<ref name="Podsakoffal2016"/> and modelling concepts in Wikidata could help to build less ambiguous concepts. Concept definition encompass various aspects such as the nature of the phenomenon, its characteristics, the links with prototypical cases or examples, the contrast with other concepts, the links with causes and consequences...<ref name="Podsakoffal2016">{{Cite Q|Q141609106}}</ref>, and scholars have advised to take insight from philosophy to work on concepts<ref>{{Cite Q|Q141609085}}</ref>. We thus read work in cognitive science which was summarizing psychology and philsosophy approaches on the determination of the content of concepts.{{Cite Q|Q141622252}} We summarize these approaches below and examine which wikidata properties exist to represent them. *Definition: the content of a concept can be formed by its decomposition into other concepts. Many Wikidata properties can be relevant to model definitions, for example: {{Wikidata entity link|P1269}}, {{Wikidata entity link|P361}}/{{Wikidata entity link|P527}}, {{Wikidata entity link|P2670}}, {{Wikidata entity link|P1552}}/{{Wikidata entity link|P6477}}, {{Wikidata entity link|P3712}}... *Categorization: the content of a concept is formed by its illustration by an exemplar (a [[wikipedia:Prototype_theory|prototype]]) that best represent the concept. (The closer a phenomenon is to the prototype, the more likely it belong to the category). Apart from the inclusion of images to illustrate an item, Wikidata structure do not highlight exemplars. However, properties signifying relations of categorizations are among the most used with {{Wikidata entity link|P31}} and {{Wikidata entity link|P279}} (see discussion here https://www.wikidata.org/wiki/Help:Basic_membership_properties). *Theory: the content of a concept is formed by its role in providing explanation of the world. Wikidata includes several properties to describe causal relationships: {{Wikidata entity link|P828}}/{{Wikidata entity link|P1542}}, {{Wikidata entity link|P1537}}/{{Wikidata entity link|P1479}}, {{P|1478}}, {{P|P9353}} (see discussions here : https://www.wikidata.org/wiki/Help:Modeling_causes/en). *Essence: the content of a concept is "something" deep explaning the entity's existence and its properties. We can use concepts before knowing what they mean, and this is what allows us to revise our knowledge about it. The idea of essence is well represented by the QID of Wikidata entities: it is independent of language and definitions and we can use it before really knowing what its properties will be. *Origin: the content of the concept is determined causally by social and historial factors (e.g. someone inventing the concept and introducing its use in a language community). This can be represented by the property {{Wikidata entity link|P3938}}. ==== Testing concept modelling on {{Wikidata entity link|Q14944319}} ==== To test concept modelling, we started by experimenting with the concept of {{Wikidata entity link|Q14944319}}. We selected a subset of papers which had energy democracy as main topic : *{{Wikidata entity link|Q137901202}} *{{Wikidata entity link|Q137901196}} *{{Wikidata entity link|Q137901182}} *{{Wikidata entity link|Q136447761}} *{{Wikidata entity link|Q129652515}} *{{Wikidata entity link|Q114306483}} We read each paper and used them as source in manually entered statements in the item {{Wikidata entity link|Q14944319}}. For example, Droubi et. Al stated "Energy democracy is both an ideal and a process"<ref>{{Cite Q|Q137901182}}</ref>, we thus entered the wikidata statement {{Wikidata entity link|Q14944319}} is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q840396}} and {{Wikidata entity link|Q3249551}}, using the paper as reference (see screenshot below). The result of this first step is visible in the archival version of the item (22 May 2026) here https://www.wikidata.org/w/index.php?title=Q14944319&oldid=2495982191. [[File:Wikidata statement- energy democracy is an instance of ideal.png|915x915px|border]] We listed the difficulties encountered as we worked and we also asked the Wikidata community to give us feedback on our modelling on the item discussion page (https://www.wikidata.org/wiki/Talk:Q14944319). These issues were related to contradictions, precision, concision and ontology. We discuss each issue and draft recommandations to refine our modelling process. ===== Contradictions ===== Wikidata contributor's feedback highlighted some apparent contradictions (The values in "does not have effect" seems contrary to what is listed in "has goal".) We would however argue this is not a problem because "statements essentially point to referenceable sources of information and different sources may provide contradicting information, it's possible to represent a plurality of perspectives on Wikidata"<ref>{{Cite web|url=https://www.wikidata.org/wiki/Help:Statements#Plurality_and_consensus|title=Help:Statements - Wikidata|website=www.wikidata.org|language=en|access-date=2026-06-08}}</ref>. Wikidata essentially supports epistemic pluralism : different worldviews can be represented in wikidata<ref name="DoğanPatel-Schneider2025">{{Cite Q|Q141613019}}</ref>, as long as they are supported by references.<ref>{{Cite Q|Q112038343}}</ref> Besides, in the case of goals versus effects statements, it is not contradictory because one can have a goal and fail to achieve it. In the case of energy democracy, some authors specifically critique the discrepancy between the movement's stated goals and what it actually achieves.<ref name="Droubial2022"/> Recommandations : Contradictions are allowed in Wikidata. ===== Precision ===== We noted that conceptual modelling requires an important degree of formalization and precision. This is a key advantage of Wikidata to be able to create links toward precise concepts which have their own identifiers. For example, we were able to create statements about specific laws and their unique identifiers in legal databases (e.g. {{Wikidata entity link|Q139764294}} and its identifier in the EUR-Lex database). However, the sources we are working with are not always precise enough and when concepts are not precisely defined, statements cannot be modelled correctly. For example, in the sentence "management of social affairs by voluntary and self-governing associations is deemed to ensure that both citizen choice and public welfare are best served"<ref>{{Cite Q|Q129652515}}.</ref>, "choice" could refer to {{Wikidata entity link|Q111986453}}, {{Wikidata entity link|Q1331926}}, {{Wikidata entity link|Q12888920}}... We can see here that academic texts are using natural language and thus are using ambiguous terms. As a result, we received feedbacks regarding a lack of precision in our statements (too many and too vague statements). In addition to the ambiguity of sources, a reason why we ended up with very general statements is because we avoided the creation of new Wikidata items. While following this implicit rule allowed us to focus on the most notable concepts, creating new items could also help make the statements more precise. Recommandations : If a concept is ambiguous it should not be included in the modelled statements. Create more precise relevant concepts if they do not exist in Wikidata. [[File:Wikidata visualisation screenshot of subclasses relationships including the item political concept.png|thumb|298x298px|Subclass relationships between "concept" and "political concept".]] ===== Concision ===== Wikidata contributor's feedback indicated a lack of concision. Some of it coming from the fact that some values were "in the tree of another value". The rule we take from this feeback is a need of logical simplification. Two examples illustrate possible logical simplification : *We stated that {{Wikidata entity link|Q14944319}} was an {{Wikidata entity link|P31}} {{Wikidata entity link|Q33104069}} and an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}. But in that case, it is not necessary to state that it is an {{Wikidata entity link|P31}} {{Wikidata entity link|Q151885}}, because {{Wikidata entity link|Q33104069}} is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q131362181}}, which is a {{Wikidata entity link|P279}} {{Wikidata entity link|Q151885}} (see diagram on the right). Here, we have to keep only the more precise item. This reasonning is based on the assumption that {{Wikidata entity link|P279}} is transitive. It seems this reasonning could be generalized (we opened a discussion about this here https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning/Use_cases#Parcimonious_statement_constraints_based_on_subclass_of_(P279)_and_part_of_(P361)_transitivity<nowiki/>) The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize this kind of relationship (using "instance of" as transversal property and checking "instance of or subclass of"). *We stated that {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P2670}} {{Wikidata entity link|Q15991216}} and {{Wikidata entity link|Q113514984}}. But if we consider that {{Wikidata entity link|Q15991216}} is a {{Wikidata entity link|P279}} of {{Wikidata entity link|Q113514984}}, then the inclusion of {{Wikidata entity link|Q15991216}} is implied. Here we could keep only the broader item {{Wikidata entity link|Q113514984}}. But unlike the reasonning above, we could not identify a way to generalize this reasonning. For example, {{Wikidata entity link|Q113514984}} can be a subclass of {{Wikidata entity link|Q43229}}, but using the former item is more informative than using the later. For the property {{Wikidata entity link|P2670}}, using a value that is too precise results in too many statements and using a value that is too general results in too trivial statements. Choosing the degree of precision is a problem similar to choosing whether or not to create a new item. Recommandations : When possible, use logical simplification to make statements more parcimonious. The [https://angryloki.github.io/wikidata-graph-builder/ Wikidata graph builder] is usefull to visualize redundancies. ===== Quantification ===== Modelling quantitative statements was challenging. We mostly skipped those but made an attempt for one case : the paper {{Wikidata entity link|Q137901196}} states that "9.8% of the final energy consumed in developing countries comes from modern renewable energy sources".<ref>{{Cite Q|Q137901196}}.</ref> Modelling this sentence by adding a statement in the item {{Wikidata entity link|Q177323}} would require creating a specific property for "final energy consumption". There are such properties in Wikidata : for example, for renewable energy subsidies, there is {{Wikidata entity link|P6826}}. This type of property is notably useful to display information about an item (e.g. the population of a town) on Wikipedia through dynamic infoboxes that are updated with Wikidata information. But the current informal rule on Wikidata property creation is to prefer the use of general properties and avoid the creation of specific properties. Therefore creating properties for every quantifiable characteristic may not be possible, nor desirable. An alternative way to model quantity is to create a specific item to represent what is quantified and use other properties to represent quantities (see example below). [[File:Wikidata screenshot of percentage modelling.png|border|783x783px]] Since Wikidata is optimized for statements with a few discrete values, it is also more convenient to store quantitative (tabular) data elsewhere<ref>{{Cite journal|last=Larrañaga|first=Galder Gonzalez|last2=Pintscher|first2=Lydia|last3=Ainali|first3=Jan|last4=Fauconnier|first4=Sandra|date=July 2026|title=Tabular data vs structured data.pptx|url=https://docs.google.com/presentation/d/1k37UX-VPwMgJbXoB7ZxsztE5LdKR_isM|journal=Wikimania 2026}}.</ref>. It is also possible to link the item that is quantified to an external dataset about it. This can be done using the property {{Wikidata entity link|P1325}}. Since our aim is not to display or analyse quantitative data, we opted for this last solution. Recommandation : Use existing properties for the quantity if it exists. If it does not exist, create an item representing what is measured and link it toward an external datasets containing the quantitative data. ===== Ontology ===== Ultimately, several of our difficulties were linked to some ontology challenges reflecting the complexity of the concept we were working on. According to the litterature, {{Wikidata entity link|Q14944319}} refer to multiple types of entities. It represents a concept, an ideal, a process and an outcome. We reflected this with multiple {{Wikidata entity link|P31}} statements, but encountered struggles to model differences between ''process versus outcomes'', ''ideal versus reality'', ''phenomenon versus theory'' and ''discourses versus practices''. The wikidata community recommands having different items for ''process and outcome'' (criterion "{{Wikidata entity link|Q127270577}}"). For example, {{Wikidata entity link|Q11629}} (practice of applying paint) is different from {{Wikidata entity link|Q3305213}} (visual artwork). However, this distinction is less straightforward for social processes which are are ongoing and evolving without a clear ending. Another problem was to separate ''ideal versus reality,'' we used {{Wikidata entity link|P3712}} to describe ideals and {{Wikidata entity link|P2670}} to describe processes attempting to reach it. It was also difficult to separate ''phenomenon versus theory,'' for example, we did not manage to model the idea that the literature on energy democracy is fragmented. Finally, we also would have needed more distinctions between ''discourses and practices.'' Our sources suggested that energy democracy discourses and practices may have different causes, we used {{Wikidata entity link|P3938}} to indicate the origins of the concept or the movments promoting it, but this was not a very precise way to model this idea. Our first attempt to multiple "natures" of energy democracy into a single item is not satisfactory, and implementing the modelling recommandations we identified above may not be sufficient to build more parcimonious statements. Creating new items to reflect the different aspects of energy democracy may here be necessary. To do so we have to decide how to split the different natures {{Wikidata entity link|Q14944319}} and what will be the relationship between the resulting items. Here the definition of an {{Wikidata entity link|Q324254}} (formal representation) in Wikidata can quickly escalate into questionning {{Wikidata entity link|Q44325}} (metaphysical reflexion on the nature of things), and especially {{Wikidata entity link|Q1713511}} (the nature of the social world). Indeed, the relations between the different types of entities constituting the social worls are not simple nor consensual among philosophers of social science. For example, {{Wikidata entity link|Q15080858}} posits that different things have different ways of being (modes of reality). They propose to classify entities in four categories : material entities (that can exist independently of humans), conceptual entities (concepts, discourses, ideas, meaning…), artefactual entities (human-made and combining conceptual and material elements) and social entities (that depends on human activity to exist)<ref>{{Cite Q|Q141612935}}.</ref>. A complex concept like {{Wikidata entity link|Q14944319}} is concerned with all these types of entities. The energy system include many material entities such as oil fields, the sun, seas, trees... and artefacts such as energy production unit, power lines, home appliances, trucks... (Including conceptual entities such as the name of these artefacts or the knowledge to make them function.). There are the social entities in which they are encompassed (the enregy sectors, energy businesses, energy policies...). There are conceptual entities like normative/political discourses discussing how these artefact and social system should work and there are conceptual entities in the academic sphere building theories about how all this works or should work. In theory, such ontology can be implemented in Wikidata as it "supports multiple coexisting classification" and allow multiple ontological frameworks to coexist.<ref name="DoğanPatel-Schneider2025"/> Current Wikidata ontology is structured with dischotomies such as {{Wikidata entity link|Q7048977}}/{{Wikidata entity link|Q4406616}}, {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}}, {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q23958946}}, {{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}}, {{Wikidata entity link|Q30241068}}/{{Wikidata entity link|Q3799040}}... A quick search seem to show that entities related to the social reality can quickly fall into heterogeneous and sometime contradictory root classes (see table below). {| class="wikitable" |+ !Item !Existing root class entity |- |{{Wikidata entity link|Q190539}} |{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q67518978}} |- |{{Wikidata entity link|Q34770}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q9081}} |{{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q43229}} |{{Wikidata entity link|Q99527517}}{{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q103940464}} |- |{{Wikidata entity link|Q49773}} |{{Wikidata entity link|Q67518978}}/{{Wikidata entity link|Q103940464}} {{Wikidata entity link|Q99527517}} {{Wikidata entity link|Q30241068}} {{Wikidata entity link|Q7048977}} |- |{{Wikidata entity link|Q12705}} |{{Wikidata entity link|Q4406616}}/{{Wikidata entity link|Q7048977}} {{Wikidata entity link|Q1970309}}/{{Wikidata entity link|Q16686448}} {{Wikidata entity link|Q99527517}}/{{Wikidata entity link|Q132907471}} |} Current {{Wikidata entity link|Q3882785}} in Wikidata do not seem very informative to classify the aspects of our concept in a top-down manner. We discussed with the Wikidata community<ref>{{Cite web|url=https://www.wikidata.org/wiki/Wikidata_talk:WikiProject_Ontology#Social_ontology|title=Wikidata talk:WikiProject Ontology - Wikidata|website=www.wikidata.org|language=en|access-date=2026-07-28}}</ref> and explored existing ontologies that could be relevant to our project. Some colleagues social science and humanities recommended CIDOC-CRM (https://cidoc-crm.org/crmsoc/fm_releases) because of the active community maintaining it. The conclusion of this exploration is that Wikidata, because of its collaborative nature, may not be the best plateform to implement a rigorous, interoperable, high-level ontology. We thus decided to focus on a lower ontological level. === Knowledge modelling in Wikidata : second round of analysis === Our first round of analysis resulted in : * Add links to exported files + insert graphs screenshots After our first round of analysis, we decided to focus on the strenghs of wikidata, which seem to be its ability to be a hub for concepts linked to external identifiers. We reframed our modelling goals to focus on identifying the main concepts in our corpus, their definition, their relationships, and their potential existing identifiers. Our next steps are * Read articles of the corpus again and model more precise statements * Include pages in references * Create new items to reflect the different facets of {{Wikidata entity link|Q14944319}} : the social movement advocating for it, the political concept theorizing it, the concrete initiatives implementing it, the litterature theorizing it, etc... based on a new reading of our sample of article and aligned with existing ontologies. We started by relying on {{Wikidata entity link|Q136447761}}, which states more clearly the different facets of {{Wikidata entity link|Q14944319}}. We kept the first item {{Wikidata entity link|Q14944319}} as the main conceptual entity, representing the ideal of energy democracy as a goal. We created other items such as {{Wikidata entity link|Q141224129}} to represent the social movement advocating for energy democracy, {{Wikidata entity link|Q141224695}} to represent policies havin energy democracy as goal, {{Wikidata entity link|Q141223998}} to represent the scholarly study of energy democracy (to separate ''phenomenon versus theory)'', {{Wikidata entity link|Q141224432}} to represent energy democracy as an outcome (to separate ''process versus outcome).'' Creating these different facets of {{Wikidata entity link|Q14944319}} allowed more precise modelling. Then existing statements were sorted to match the different types of entity. For example, {{Wikidata entity link|Q3109572}} was linked to {{Wikidata entity link|Q141224129}} and {{Wikidata entity link|Q1951366}} to {{Wikidata entity link|Q141224695}}. To reflect the dimensions of the concept of {{Wikidata entity link|Q14944319}}, we used {{Wikidata entity link|P527}}. For example, the sentence "Becker and Naumann list decentralized energy generation, public and cooperative ownership and energy sovereignty as the dimensions of energy democracy<ref>{{Cite Q|Q139492906}}</ref><ref>{{Cite Q|Q136447761}}</ref>, was modeled as {{Wikidata entity link|Q14944319}} {{Wikidata entity link|P527}} : {{Wikidata entity link|Q861135}}, {{Wikidata entity link|Q119080352}}, {{Wikidata entity link|Q4227971}} and {{Wikidata entity link|Q130487674}}. We removed some statements, following logical simplifications. For example, there is no need to mention the broad concept of {{Wikidata entity link|Q6498684}}, while there are mentions of more precise concepts such as {{Wikidata entity link|Q119080352}} and {{Wikidata entity link|Q4227971}}. == 3. Data visualisation == The goal of this step is to test '''Hypothesis 3''' (SPARQL-based queries and visualizations can be used to navigate  scientific corpora and scientific knowledge graphs). At this stage we started to identify visualization use cases we would like to test, they are listed below. === Filter statements === *Visualize only items which are part of the present project (all the academic items of the project include the statement {{Wikidata entity link|P6104}} {{Wikidata entity link|Q134545539}}). === Visualize the statements supported by a specific source === * https://synia.toolforge.org/#work/Q114306483 === Properties visualisation === *Visualise the "tree" of a property used in an item : Wikidata graph builder seem to be the most user friendly, robust and versatile tool to visualise a graph of a single property (https://angryloki.github.io/wikidata-graph-builder/) [[File:Visualisation of the "instance of" values for energy democracy in Wikidata.png|center|thumb|553x553px|Visualisation of the "{{Wikidata entity link|P31}}" values for {{Wikidata entity link|Q14944319}} in Wikidata. Made with the [https://angryloki.github.io/wikidata-graph-builder/ Wikidata Graph Builder].]] === Concepts visualisation === *Map all statements related to a single item (e.g. [[d:Wikidata:Scholia|Scholia]] request "topic in context")[[File:Screenshot of Energy democracy wikidata graph.png|center|thumb|450x450px|Graph of the {{Wikidata entity link|Q14944319}} concept generated with [https://scholia.toolforge.org Scholia]'s "The topic in context" query.]]Map the statements that two items have in common to make comparisons. [[File:Community energy and energy democracy.png|center|thumb|440x440px|Data visualisation of the concepts of {{Wikidata entity link|Q14944319}} and {{Wikidata entity link|Q113514984}}. Made with [https://think.resoneo.com/wikidata-search/ Wikidata Knowledge Explorer] .]]Find the relationships between two concepts. === Mapping sources consensus === *Queries can help visualize which concept is central across sources : https://query.wikidata.org/#%23defaultView%3AGraph%0ASELECT%20%0A%20%20%3Fvalue%20%3FvalueLabel%20%3Fpublication%0A%0AWHERE%20%7B%0A%20%20wd%3AQ14944319%20%3Fp%20%3Fobject_statement%20.%0A%20%20%3Fobject_statement%20prov%3AwasDerivedFrom%20%3Freference%20%3B%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3Fps%20%20%3Fvalue%20.%0A%20%20%3Fvalue%20rdfs%3Alabel%20%3FvalueLabel%20.%0A%20%20FILTER%20%28lang%28%3FvalueLabel%29%20%3D%20%27en%27%29%0A%20%20%3Freference%20pr%3AP248%20%3Fpublication%20.%0A%7D[[File:Link between concepts and references in the Energy Democracy wikidata item.png|center|thumb|396x396px|Link between concepts and references in the Energy Democracy wikidata item.]] *Visualise graphs and use the number of references to determine edge thickness/weight in order to make consensual statements more visible.[[File:Number of references supporting statements about a chain of contributing factors of energy democracy.png|center|thumb|454x454px|Visualisation of the number of references supporting statements about the chain of contributing factors of energy democracy.]] == 4. Writing == The goal of this step is to test '''Hypothesis 4''' (Wikiversity pages can be used to write literature reviews collaboratively in text format augmented by interwiki links). * To do idea : write a Wikiversity page for each central concept (e.g. energy democracy, energy community, energy citizenship...) === Advantages of Wikiversity === Writing on a Wikiversity page offers some advantages to implement the principles of open linked data in text format. We could cite academic items using their Wikidata QID to generate the citations below (but if we use an URL to cite a paper, it does not automatically check if there is an existing QID for it), and also link toward Wikidata entities using a template ([[Template:Wikidata entity link|Wikidata entity link]]). Although we did not translate the present page for now, Wikiversity offers the possibility to translate a page in multiple languages (an interesting possibility in the context of the The FAIRisation of scholarly communication).<ref>{{Cite Q|Q110684311}}</ref> The possibility to view the page history provide an exhaustive versionning of a paper, which constitute interesting data documenting the academic writing process (at first we did not comment the nature of our modifications but after thinking about this reuse possibility, we described it with more details). The contribution statistics based on the history also offers a new way to track author's contributions to a paper in a transparent way. Some researchers experimented relationships between the wikimedia community and researchers by making researchers review wikipedia articles.<ref>{{Cite Q|Q136659684}}.</ref> === The issue of text interoperability === A key issue we are encountering is the question of the interoperability of texts. While the interoperability of data is starting to be well discussed in the open science community, the interoperability of texts do not seem to benefit from the same level of discussion. We encountered several interoperability issues regarding our writing. First, copying texts written on a word processor software (e.g. microsoft word) into a wiki page (or the other way around) is relatively seamless in terms of formatting, but the management of references is lacking. Reformatting references is very time consuming and a real barrier for text interoperability in academic context : it is difficult to copy text from an academic publication into a wiki text, and difficult to turn a wiki text into a publication (the only possibility is to export the page as a PDF and you may be reading this article in this format). There are also uncertaineties regarding how to reuse texts published under creative common licences. Academic texts published under CC-BY-SA licences can in theory be remixed and reused. But academia does not have established practices regarding how this can be done. If we want to reuse a whole page, should we put it in quotation marks and simply cite the paper ? Should the original authors be listed as co-authors ? To what extent academic publisher will accept to publish "remixed" texts while they usually require that publications contain mainly unpublished content ? The norms of what is appropriate remix and reuse practices in academia has yet to be decided... and this could be an interesting conversation to have in the open science community. == Discussion == Our goal was to assess the potential of Wikidata and Wikiversity to build a living literature review method and tackle issues of information overload, knowledge synthesis and knowledge dissemination, following open science principles. By conducting a meta-review on just sustainability transition (that is a review of existing literature reviews), and experimenting with existing technical solutions, we were able to identify the strenghs and limitations of the Wikidata ecosystem. First Wikidata can be used to enrich scientific item metadata and build living scientific corpora with rich annotations (Hypothesis 1 is verified). However, the technical barriers to do so are still high and the Wikidata database is too general to allow a community to work on a specific curated corpus of scientific items. Secondly, Wikidata can be used for scientific knowledge modeling through statements using scientific items as reference (Hypothesis 2 is verified). However, this requires developping new methodological standards regarding what is a rigorous modelling in social science, as well as building specific {{Wikidata entity link|Q324254}}. An unexpected finding is that the formalization necessary for knowledge modelling in wikidata invites to formalize the reasonning behind modelling choices, a process that is rarely done in qualitative analysis even though such reasonning are likely present. The modelling process also responds to calls in management sciences to engage in more systematic categorizing to avoid semantic confusion.<ref>{{Cite Q|Q141609095}}.</ref> Thirdly, SPARQL-based queries can be used to vizualised scientific corpora and scientific knowledge graphs, but we cannot completely say they allow users to "navigate" it (Hypothesis 3 is partially verified). SPARQL-based queries are powerful but they require technical knowledge, especially now that the split between academic and non-academic items in Wikidata requires to write federated queries. To be able to "navigate" scientific corpora and scientific knowledge graphs on Wikidata, more user-friendly tools would be needed. Finally, we did see advantaged in using Wikiversity pages to write collaboratively in text format augmented by hypertext links, but there are still important technical and instittional barriers (Hypothesis 3 is partially verified) : the interoperability of text is a key issue to reuse publications. The main issues we encountered were the management of references and uncertainty regarding the compatibilities between writing publicly on a wiki page and engaging in classical publication processes. A potential solution to the issues encountered could be to develop a specialised literature review software that would allow researchers to build living literature reviews including knowledge graphs and wiki pages. This kind of tool should be user-friendly and include the missing tools we identified. In addition, it could include more advanced analysis functions such as logical reasonning based on the knowledge graph.<ref name="Hoganal2022"/> === Quality assessment === <ref>{{Cite Q|Q141622289}}</ref> Methods for assessing Wikidata's data quality are still under development: following the questions raised by Piscopo and Simperl about the accuracy and reliability of the data<ref>{{Cite Q|Q66776851}}.</ref>, Shenov et al. (2022) propose a framework combining several indicators to detect low-quality statements, revealing issues such as duplicate entities, missing triples, and unmet constraints.<ref>{{Cite Q|Q107425133}}</ref> Two studies address the quality of ''referencing'' in Wikidata — that is, the reliability of sources cited to support claims — a distinct but complementary aspect of data quality itself. Amaral et al. (2021)<ref>{{Cite Q|Q112038343}}.</ref> use a mixed-methods approach (crowdsourcing, statistics, machine learning) to assess the relevance, accessibility, and authority of Wikidata's references at scale and across languages. Beghaeiraveri et al. (2023) build on this by proposing the RQSS, a system that quantifies referencing quality through scores, allowing contributors and project leads to identify and fix gaps.<ref>{{Cite Q|Q130478432}}</ref> Together, these works mark a shift from exploratory assessment of reference quality toward standardized measurement tools — though this raises the question of whether a numerical score can adequately capture a notion as contextual as a source's "authority". The community develops tools for detecting vandalism (intentional additions of low-quality contributions), relying on machine learning approaches adapted to the specific features of RDF triples, up to the current deployment of the ORES service in Wikidata.<ref>{{Cite Q|Q27579144}}.</ref><ref>{{Cite Q|Q28942543}}</ref> === Future research === - Can we "reason" with Wikidata (See: https://www.wikidata.org/wiki/Wikidata:WikiProject_Reasoning) : neurosymbolic AI ? - Compare grounded theory/CAQDAS with knowledge modelling methods, test annotation softwares : https://inception-project.github.io/ ; https://pacte.crim.ca/index_en.html ==== Supporting inductive research ==== Inductive research with an empirical phenomenon and then use of abstract concepts to describe it, a process called “Framing”, theorizing or conceptualizing.<ref name="CasanaveLi2015">{{cite Q|Q141609034}}</ref> Conceptualization require to answer the question « what are our data examples of? ».<ref name="CasanaveLi2015"/> This step is particularly challenging in inductive research since the same empirical phenomenon can be described through different concepts that leads to different perspectives or lenses the phenomenon and will refer to different theoretical traditions or disciplines.<ref name="CasanaveLi2015"/> Building a collection of concepts and their relationship to specific concrete cases in Wikidata could support inductive process by giving researchers access to relevant conceptualizations made by others. == Funding == This project is funded by the [[m:Grants:Programs/Wikimedia_Research_&_Technology_Fund/Wikimedia_Research_Fund|Wikimedia Research Fund]], Grant ID: G-RS-2504-18935. The text of the initial research proposal is available here : https://doi.org/10.5281/zenodo.20760603. == Data == {| class="wikitable sortable" ! QID !! Year !! DOI !! Title |- | [[d:Q137901191|Q137901191]] || 2025 || [https://doi.org/10.1002/GEO2.70040 10.1002/GEO2.70040] || Place-Based Sustainability Transformations for Just Futures: A Systematic Review |- | [[d:Q137901187|Q137901187]] || 2025 || [https://doi.org/10.1002/WCC.932 10.1002/WCC.932] || Public Communication of Climate and Justice: A Scoping Review |- | [[d:Q135979013|Q135979013]] || 2025 || [https://doi.org/10.1007/S13280-025-02202-Z 10.1007/S13280-025-02202-Z] || Participatory approaches to climate adaptation, resilience, and mitigation: A systematic review |- | [[d:Q137901223|Q137901223]] || 2022 || [https://doi.org/10.1007/S13412-021-00726-W 10.1007/S13412-021-00726-W] || A review of stakeholder participation studies in renewable electricity and water: does the resource context matter? |- | [[d:Q137901184|Q137901184]] || 2021 || [https://doi.org/10.1007/S40518-021-00184-6 10.1007/S40518-021-00184-6] || Energy Storage as an Equity Asset. |- | [[d:Q114204627|Q114204627]] || 2021 || [https://doi.org/10.1007/S43621-021-00024-Z 10.1007/S43621-021-00024-Z] || Can public awareness, knowledge and engagement improve climate change adaptation policies? |- | [[d:Q137901209|Q137901209]] || 2026 || [https://doi.org/10.1016/J.AGSY.2025.104512 10.1016/J.AGSY.2025.104512] || Designing with non-humans for agricultural systems transformation: An interdisciplinary review and framework for reflection |- | [[d:Q137901201|Q137901201]] || 2025 || [https://doi.org/10.1016/J.COPSYC.2024.101987 10.1016/J.COPSYC.2024.101987] || Individual and community catalysts for Renewable Energy Communities (RECs) development |- | [[d:Q114197507|Q114197507]] || 2022 || [https://doi.org/10.1016/J.CRM.2022.100438 10.1016/J.CRM.2022.100438] || Advancements of sustainable development goals in co-production for climate change adaptation research |- | [[d:Q129203992|Q129203992]] || 2024 || [https://doi.org/10.1016/J.EGYR.2024.01.040 10.1016/J.EGYR.2024.01.040] || Empowering energy citizenship: Exploring dimensions and drivers in citizen engagement during the energy transition |- | [[d:Q137901216|Q137901216]] || 2026 || [https://doi.org/10.1016/J.EIAR.2025.108187 10.1016/J.EIAR.2025.108187] || From participation to partnership: A systematic review of public engagement in sustainable urban planning |- | [[d:Q137210566|Q137210566]] || 2016 || [https://doi.org/10.1016/J.ERSS.2015.10.004 10.1016/J.ERSS.2015.10.004] || Energy justice: A conceptual review |- | [[d:Q115448818|Q115448818]] || 2016 || [https://doi.org/10.1016/J.ERSS.2016.04.001 10.1016/J.ERSS.2016.04.001] || Stakeholder involvement in sustainability science—A critical view |- | [[d:Q129652515|Q129652515]] || 2018 || [https://doi.org/10.1016/J.ERSS.2018.06.010 10.1016/J.ERSS.2018.06.010] || What is energy democracy? Connecting social science energy research and political theory |- | [[d:Q137901196|Q137901196]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101716 10.1016/J.ERSS.2020.101716] || Of renewable energy, energy democracy, and sustainable development: A roadmap to accelerate the energy transition in developing countries |- | [[d:Q136447761|Q136447761]] || 2020 || [https://doi.org/10.1016/J.ERSS.2020.101768 10.1016/J.ERSS.2020.101768] || Energy democracy as a process, an outcome and a goal: A conceptual review |- | [[d:Q137901204|Q137901204]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101834 10.1016/J.ERSS.2020.101834] || Identities, innovation, and governance: A systematic review of co-creation in wind energy transitions |- | [[d:Q137901183|Q137901183]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101837 10.1016/J.ERSS.2020.101837] || Renewable energy for whom? A global systematic review of the environmental justice implications of renewable energy technologies |- | [[d:Q137901207|Q137901207]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101871 10.1016/J.ERSS.2020.101871] || Rethinking community empowerment in the energy transformation: A critical review of the definitions, drivers and outcomes |- | [[d:Q137901215|Q137901215]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101876 10.1016/J.ERSS.2020.101876] || Co-production in the wind energy sector: A systematic literature review of public engagement beyond invited stakeholder participation |- | [[d:Q114306511|Q114306511]] || 2021 || [https://doi.org/10.1016/J.ERSS.2020.101907 10.1016/J.ERSS.2020.101907] || From consultation toward co-production in science and policy: A critical systematic review of participatory climate and energy initiatives |- | [[d:Q137901221|Q137901221]] || 2021 || [https://doi.org/10.1016/J.ERSS.2021.102257 10.1016/J.ERSS.2021.102257] || The challenges of engaging island communities: Lessons on renewable energy from a review of 17 case studies |- | [[d:Q137901218|Q137901218]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102333 10.1016/J.ERSS.2021.102333] || The (in)justices of smart local energy systems: A systematic review, integrated framework, and future research agenda |- | [[d:Q137901182|Q137901182]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102444 10.1016/J.ERSS.2021.102444] || A critical review of energy democracy: A failure to deliver justice? |- | [[d:Q114306483|Q114306483]] || 2022 || [https://doi.org/10.1016/J.ERSS.2021.102482 10.1016/J.ERSS.2021.102482] || The role of energy democracy and energy citizenship for participatory energy transitions: A comprehensive review |- | [[d:Q114306476|Q114306476]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102714 10.1016/J.ERSS.2022.102714] || What about citizens? A literature review of citizen engagement in sustainability transitions research |- | [[d:Q137901193|Q137901193]] || 2022 || [https://doi.org/10.1016/J.ERSS.2022.102862 10.1016/J.ERSS.2022.102862] || When energy justice is contested: A systematic review of a decade of research on Sweden?s conflicted energy landscape |- | [[d:Q137901219|Q137901219]] || 2023 || [https://doi.org/10.1016/J.ERSS.2022.102913 10.1016/J.ERSS.2022.102913] || Can we optimise for justice? Reviewing the inclusion of energy justice in energy system optimisation models |- | [[d:Q137901186|Q137901186]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103010 10.1016/J.ERSS.2023.103010] || Analysing intersections of justice with energy transitions in India- A systematic literature review |- | [[d:Q137901181|Q137901181]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103053 10.1016/J.ERSS.2023.103053] || Fostering justice through engagement: A literature review of public engagement in energy transitions |- | [[d:Q137211155|Q137211155]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103213 10.1016/J.ERSS.2023.103213] || A fairway to fairness: Toward a richer conceptualization of fairness perceptions for just energy transitions |- | [[d:Q137901217|Q137901217]] || 2023 || [https://doi.org/10.1016/J.ERSS.2023.103221 10.1016/J.ERSS.2023.103221] || Powering just energy transitions: A review of the justice implications of community choice aggregation |- | [[d:Q137901199|Q137901199]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104016 10.1016/J.ERSS.2025.104016] || Making energy renovations equitable: A literature review of decision-making criteria for a just energy transition in residential buildings |- | [[d:Q137901188|Q137901188]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104036 10.1016/J.ERSS.2025.104036] || Community energy justice: A review of origins, convergence, and a research agenda |- | [[d:Q137901211|Q137901211]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104067 10.1016/J.ERSS.2025.104067] || Psychological and social factors driving citizen involvement in renewable energy communities: A systematic review |- | [[d:Q137901192|Q137901192]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104149 10.1016/J.ERSS.2025.104149] || Assessing social impacts and Energy Justice along green hydrogen supply chains: a capability-based framework |- | [[d:Q137901195|Q137901195]] || 2025 || [https://doi.org/10.1016/J.ERSS.2025.104422 10.1016/J.ERSS.2025.104422] || Out of place, scale and time? Navigating injustices across mission arenas of the German Energiewende |- | [[d:Q137901185|Q137901185]] || 2024 || [https://doi.org/10.1016/J.ESD.2024.101546 10.1016/J.ESD.2024.101546] || Characterizing 'injustices' in clean energy transitions in Africa |- | [[d:Q137901226|Q137901226]] || 2024 || [https://doi.org/10.1016/J.JCLEPRO.2024.143470 10.1016/J.JCLEPRO.2024.143470] || Energy justice and sustainable urban renewal: A systematic review of low-income old town communities |- | [[d:Q137901222|Q137901222]] || 2024 || [https://doi.org/10.1016/J.JENVMAN.2024.120804 10.1016/J.JENVMAN.2024.120804] || Forest, climate, and policy literature lacks acknowledgement of environmental justice, diversity, equity, and inclusion |- | [[d:Q115441381|Q115441381]] || 2021 || [https://doi.org/10.1016/J.RSER.2021.111504 10.1016/J.RSER.2021.111504] || Participatory methods in energy system modelling and planning – A review |- | [[d:Q137901205|Q137901205]] || 2025 || [https://doi.org/10.1016/J.RSER.2025.115892 10.1016/J.RSER.2025.115892] || A systematic review of the intersection between energy justice and human rights |- | [[d:Q137901225|Q137901225]] || 2024 || [https://doi.org/10.1017/SUS.2024.24 10.1017/SUS.2024.24] || Blue carbon as just transition? A structured literature review |- | [[d:Q137901220|Q137901220]] || 2025 || [https://doi.org/10.1017/SUS.2025.2 10.1017/SUS.2025.2] || Toward an intersectional equity approach in social-ecological transformations |- | [[d:Q137901203|Q137901203]] || 2024 || [https://doi.org/10.1080/14693062.2023.2256697 10.1080/14693062.2023.2256697] || Exploring the democracy-climate nexus: a review of correlations between democracy and climate policy performance |- | [[d:Q137901164|Q137901164]] || 2022 || [https://doi.org/10.1111/GEC3.12662 10.1111/GEC3.12662] || Creating fairer futures for sustainability transitions |- | [[d:Q137901227|Q137901227]] || 2025 || [https://doi.org/10.1139/ER-2024-0018 10.1139/ER-2024-0018] || Community engagement in nature-positive food systems programming and research in East and Southern Africa: a review |- | [[d:Q119955266|Q119955266]] || 2019 || [https://doi.org/10.1146/ANNUREV-ENVIRON-101718-033103 10.1146/ANNUREV-ENVIRON-101718-033103] || Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice |- | [[d:Q137901206|Q137901206]] || 2023 || [https://doi.org/10.1146/ANNUREV-ENVIRON-112621-063400 10.1146/ANNUREV-ENVIRON-112621-063400] || Metrics for Decision-Making in Energy Justice |- | [[d:Q137901213|Q137901213]] || 2022 || [https://doi.org/10.1186/S13705-021-00330-4 10.1186/S13705-021-00330-4] || Mapping emergent public engagement in societal transitions: a scoping review |- | [[d:Q137901163|Q137901163]] || 2025 || [https://doi.org/10.17573/CEPAR.2025.2.09 10.17573/CEPAR.2025.2.09] || From Co-Creation to Circular Cities: Exploring Living Labs in EU Governance Frameworks - A Literature Review |- | [[d:Q137901197|Q137901197]] || 2024 || [https://doi.org/10.3390/EN17143512 10.3390/EN17143512] || A Systematic Review on the Path to Inclusive and Sustainable Energy Transitions |- | [[d:Q104887325|Q104887325]] || 2019 || [https://doi.org/10.3390/SU11041023 10.3390/SU11041023] || Deliberation and the Promise of a Deeply Democratic Sustainability Transition |- | [[d:Q137901202|Q137901202]] || 2021 || [https://doi.org/10.3390/SU13042128 10.3390/SU13042128] || A Review of Energy Communities in Sub-Saharan Africa as a Transition Pathway to Energy Democracy |- | [[d:Q137901210|Q137901210]] || 2023 || [https://doi.org/10.3390/SU15032441 10.3390/SU15032441] || Sustainable Project Governance: Scientometric Analysis and Emerging Trends |- | [[d:Q137901224|Q137901224]] || 2024 || [https://doi.org/10.3390/SU16198700 10.3390/SU16198700] || Empowering Communities to Act for a Change: A Review of the Community Empowerment Programs towards Sustainability and Resilience |} == References == {{References}} bxy06yd5l35k48eqe13r66kd2upp0no 0 327555 2835347 2832837 2026-10-01T13:57:31Z DavidMCEddy 218607 /* Text and self-help book and point of discuss */ wdsmth 2835347 wikitext text/x-wiki [[File:Pharoah - James VI and I - Trump.png|thumb|Religious and media leaders from the time of the Pharaohs convinced common folk to give increasing shares of what they produced to elites.]] :''This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.'' == Invitation to edit this book == You, dear reader, are invited to contribute questions, ideas and citations to support or refute claims made in this book possibly adding chapters. Wikiversity like other Wikimedia Foundation Projects invites humans to [[w:Wikipedia:Be bold|“be bold but not reckless,”]] while writing from a [[Wikiversity:Disclosures|neutral point of view]], [[Wikiversity:Cite sources|citing credible sources]]. Others are invited to change or revert what you wrote. What stays tends to be written from a neutral point of view citing credible sources. If someone reverts your edit or you have a question, take it to the ''[[Wikiversity:FAQ|''''“Discuss”'''' page]]'' associated with the specific Wikiversity page most related to your concerns. Those who teach media literacy are encouraged to invite their students to debate and revise the contents of this book. Doing so would build on a tradition of [[:w:Wikipedia:Student assignments|instructors requiring students to edit wikipedia article(s).]] Editing [[:w:Wikipedia|Wikipedia]] and other [[:w:Wikimedia Foundation|Wikimedia Foundation]] projects like this book is itself an exercise in media literacy: :''Central tenets of media literacy might include writing from a neutral point of view citing credible sources and engaging others, some of whom may disagree, in civil, supportive conversations about what can and cannot be said based on a reasonable evaluation of the available evidence. Wikimedia rules invite contributors to do just that, encouraging them to “be bold but not reckless,” contributing revisions written from a neutral point of view, citing credible sources -- and raising other questions and concerns on the ''''“Discuss”'''' page associated with the specific Wikiversity page most related to your concerns, as mentioned above.''<ref>For more on this, see Graves (2024).</ref> == Text and self-help book and point of discuss == This book is intended both as a text and self-help book and as a point of discussion considering four levels of media literacy: :1. '''Think before you share''': [[Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen said]], "The shortest path to a click is anger or hate." The social psychology behind this phenomenon exploited also by legacy media has contributed to [[Media Literacy and You/Media consolidation, social media, and political polarization|the dramatic increase in political polarization and violence worldwide]], especially since the end of the [[w:Fairness doctrine|Fairness doctrine]] in 1987. To counter this, DiResta (2024, p. 335) recommends, "Think before you share." :2. '''Look for information to contradict preconceptions''' (Disconfirmation bias): [[w:Information is a public good: Designing experiments to improve government#Previous research|Virtually everyone]] (a) thinks they know more than they do ([[w:Overconfidence effect|overconfidence effect]]), and (b) prefers information and sources consistent with preconceptions ([[w:Confirmation bias|confirmation bias]]). The major media everywhere exploit this to please those who control most of the money for the media. Humans can counter this by searching for sources to help us understand our designated enemies. If we cannot explain circumstances under which we could see ourselves doing what we see our designated enemies doing, we haven't looked hard enough. :3. '''Talk''': Push ourselves to have friendly supportive conversations with others with whom we may vehemently disagree seeking common ground, agreeing to disagree agreeably where we differ, and building collaboration on areas of common concern.<ref>Graves and Bailey (2025).</ref> :4. '''Teach''': Humans who develop skills in the first three levels can leverage that knowledge in helping others acquire those skills. If each one teaches two<ref>"[[:w:Each one teach one|Each one teach one]]" is an African-American proverb from the time of legalized slavery. However, if each one teaches only one, the growth in literacy will only be linear. Having "each one teaching two", on average, unleashes the power of doubling and [[:w:exponential growth|exponential growth]], which has the potential of educating the entirety of humanity in a reasonable period of time -- namely after 33 doublings starting from one.</ref> in a certain period of time, that time period becomes a [[:w:Doubling time|doubling time]]. Ten doublings is a thousand -- actually 1,024 to be precise.<ref>2 time 2 = 4 times 2 = 8 times 2 = 16 times 2 = 32 times 2 = 64 times 2 = 128 times 2 = 256 times 2 = 512 times 2 = 1024: That's 10 doublings, as anyone with a modest understanding of modern digital [[:w:computer|computer]]s will tell you.</ref> Twenty doublings become a million. Thirty doublings become a billion. Three more doublings become 8 billion, the [[:w:World population|world population]] as of approximately 2022-11-15.<ref>This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.</ref> Many organizations, including several United Nations agencies, already have active [[w:media literacy|media literacy]] programs that have already trained many.<ref>''[[Wikibooks:Antiracist Activism for Teachers and Students]]'' includes a chapter on [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools|Media Literacy In Schools]].</ref> This book is being written hoping to increase the effectiveness and accelerate the rate of growth in media literacy and thereby accelerate progress against many of the most pressing issues facing humanity today. Much of this book is a [[w:Monograph|research monograph]] summarizing research that seems to have been underreported by the major media to avoid offending people who control most of the money for the media. These research results seem to be central to major political divisions. Each chapter ends in exercises to help the reader practice media literacy skills and have fun doing it. Remember: :''I am entitled to my [[Wiktionary:cockamamie|cockamamie]] ideas, and you are entitled to yours.'' Humor is important but must be offered in a way that does not offend others. If others are offended, they may be less interested in dialogue. The term "cockamamie" is used here, hoping that this style of [[w:Self-deprecation|self-deprecation]] might be more inviting for dialogue. ''Never say, "You're wrong." Instead, ask, "May I offer a contrary perspective?" Or "May I share with you another view that I've heard?"'' Much of the information in this book seems to have been largely overlooked and perhaps suppressed, apparently because it would either offend people who control substantial portions of the money for the media our would increase the cost of producing news; see the brief discussion of conflicts of interest by the major media in the next "Key claims" section. ==Key claims== * ''Primary drivers of every major conflict include differences between the media or difference in interpretation that the different parties find credible''. :-- This works, because everything we think we know is coded in systems of connections between neurons in our brains. These systems are more unique than fingerprints and evolve over time. The words we use do not mean the same to two different humans nor even to the same human at different points in time. In many cases these differences are inconsequential. ''Sometimes they are fatal.''<ref>Graves and Bailey (2026).</ref> :-- ''[[w:Social constructionism|Show me someone who knows the truth]], and I will show you someone who is dangerous'' -- especially during war or any other situation where humans may be moved to violence mandated by their belief system.<ref>[[w:Collateral damage|Collateral damage]] that "they" commit proves to "us" that "they" are subhuman or at best criminally misled and must be resisted by any means necessary. By contrast, collateral damage that "we" commit is unfortunate but necessary.</ref> * The major media everywhere have [[w:Conflict of interest|conflicts of interest ]] in honestly reporting on [[v:Information is a public good per communications prof Pickard|anything that might offend anyone who controls large portions of the money for the media]].<ref>Pickard and Graves (2025), accessed 2026-02-08; Pickard (2020).</ref> [[v:Media Reform Coalition challenges anti-democratic media bias in the UK|British journalist and media reform advocate Dan Hind]] said that the content produced by the [[w:BBC|BBC]] was frivolous, soap opera stuff, because leading media personalities know very little about issues of substance and believe "they might get in trouble if" they produced anything serious. Similar analyses seem to apply to the major media everywhere<ref>Hind and Graves (2025), accessed 2026-02-09.</ref> but may not apply to non-profit and local media, which seem more likely to produce [[w:Investigative journalism|investigative]] / [[v:Dean Starkman and the watchdog that didn't bark|accountability journalism]]:<ref>Usher and Kim-Leffingwell (2022); see also Starkman and Graves (2025), accessed 2026-02-09.</ref> [[w:Watchdog journalism|Watchdogs]] tend to protect the people who feed them. Argentine journalist [[w:Horacio Verbitsky|Horacio Verbitsky]] said, "Journalism is disseminating information that someone does not want known; the rest is [[w:propaganda|propaganda]]."<ref>p. 16 in Verbitsky (1997); English translation from [[Wikiquote:Horacio Verbitsky]], accessed 2026-02-09.</ref> * The major media everywhere create the stage upon which politicians read their lines. :-- Their selection of acceptable topics for news and entertainment create and maintain the "[[w:Overton window|Overton window]]", which is the range of acceptable political discourse. For example, in early 1964, US President [[w:Lyndon B. Johnson|Lyndon Johnson]] understood that he could lose the 1964 presidential election that year if he were seen to be soft on communism. His response was to clandestinely provoke an attack on US naval vessels in the Gulf of Tonkin, which he could then denounce as "unprovoked". During a dark and stormy night 1964-08-04 the [[w:USS Maddox (DD-731)|USS ''Maddox'']] and [[w:USS Turner Joy|''Turner Joy'']] spent a couple of hours "defending themselves" against radar snow, then [[w:Gulf of Tonkin incident|reported that they had sunk two attacking North Vietnamese torpedo boats]]; subsequent investigations found no evidence of the reported attacks. That incident was used to justify the [[w:Gulf of Tonkin Resolution|Gulf of Tonkin Resolution]], with only two dissenting votes in the US Congress: Those two dissenters were defeated in their next reelection campaigns, illustrating the point that the major media create the environment in which many politicians cannot get elected without betraying the nation. :-- Nick Hart,<ref name=Hart><!--Nick Hart-->{{cite Q|Q135663983}}</ref> President and CEO of the Data Foundation,<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> noted that President Trump in his first term signed the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]], which was bipartisan legislation ostensibly mandating evidence-informed public policy.<ref>Hart mentioned the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] when he was interviewed for [[Evidence-informed public policy|"Media & Democracy" 2025-07-31]].</ref> The evidence is clear: ::''The US Congress is effectively not allowed to consider solid research suppressed by the major media.'' * The development of technology is never neutral in its impact on inequality but is driven to benefit people with power.<ref>Acemoglu and Johnson (2023)</ref>. :-- [[Media Literacy and You/The impact of the media on political economy since the time of the Pharaohs|Improvements in agricultural technology from pre-history to the time of King James of the King James bible were managed to benefit elites.]] Then pamphlets and newspapers began to appear, the head of state stopped granting as many monopolies, and commoners began getting permission to become entrepreneurs. That transformed economic stagnation into growth in GDP per capita adjusted for inflation, initiating the [[w:Industrial Revolution|Industrial Revolution]], as documented in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]]. It also led to increasing inequality until organized labor got enough political power to demand and get a bigger share of the fruits of their labors. :--[[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|In the US those benefits peaked during the Great Depression]], when the standard conservative mantra that blames the poor for their poverty did not sell newspapers. US President Franklin Roosevelt taxed the ultra-wealthy like they had never been taxed before or since, and dramatically reduced inequality, which continued to decline until increasing concentration of ownership of the media ushered in a new era of increasing inequality starting with the presidency of Ronald Reagan. :-- [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future#Role of the media|Acemoglu and Johnson insist that technology, including artificial intelligence, can be developed to benefit all. However, but it will not happen without action by the poor and middle class as follows]]: :# Alter the narrative, :# Build countervailing powers [like organized labor], and :# Develop technical, regulatory, and policy solutions to tackle specific aspects of technology’s social bias.<ref>Acemoglu and Johnson (2023, ch. 11).</ref> :-- For more on this, see, e.g., the chapter on [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|Fox, the Great Depression, the Great Recession, and our future]]. === The value of noncommercial news outlets === Some of the problems with the media and their contributions to increasing political polarization and violence are documented in the research summary on "[[Information is a public good: Designing experiments to improve government]]" and in the podcast series available on Wikiversity under "[[:Category:Media reform to improve democracy]]" with leading experts discussing their recommendations. One of the most compelling of the references discussed in that podcast series is Usher and Kim-Leffingwell (2022), who tallied all the federal prosecutions for political corruption in each of the 94 [[w:United States federal judicial district|US federal court district]]s between 2003 and 2019. During that period, the number of journalists in the US fell by a factor of roughly 3 -- between 60 and 70 percent. They found no statistically significant impact on federal prosecutions for political corruption of that decline in the number of journalists. However, each member of the [[w:Institute for Nonprofit News|Institute for Nonprofit News]] (INN) in a federal court district in one year was associated with on average 1.4 additional prosecutions for political corruption the following year. Since federal prosecutions for political corruption averaged roughly 10 per federal court district per year during that period. each member of INN in a federal court district one year was associated with a 14 percent increase in federal prosecutions the following year. This suggests that the major media outlets that had so dramatically reduced their staffs had not substantively reduced the amount of investigative journalism they did. If we assume that the people prosecuted for political corruption also control substantive advertising budgets, then the major media outlets have conflicts of interest in honestly reporting on such. They may report on it if some other organization like a member of INN does the research and they are threatened with a loss of audience from not reporting on it. :'''''Major point''''': You and I benefit, the vast majority of humans on earth benefit, from news reports presumably published by members of INN that contributed to those on average 1.4 additional prosecutions for political corruption estimated by Usher and Kim-Leffingwell (2022). We benefit even if we never heard about the news reports that contributed to those prosecutions. We benefit even if we have never heard of the news outlets that presumably did the investigative journalism behind those additional prosecutions. Why? Because on average those news reports likely deterred other incidents of political corruption, which likely contributed to broadly shared economic growth and the development of new technology that ultimately benefit the vast majority of humanity. Other aspects of this are documented in the research on the impact of [[w:news desert|news desert]]s, which we summarize next. === Costs increase in news deserts=== There's a growing body of research describing what happens when local newspapers die. Perhaps most important, a 2018 research report by Gao et al. reported that the death of a local newspaper was followed by … increases in local tax revenue, averaging $85 per human per year.<ref name = Gao2018>Gao et al. (2018).</ref> That $85 was roughly 13 hundredths of a percent of the 2019 US GDP. That's mentioned in the 2025-07-17 interview with [[Democratic delusions: Fix the media to fix democracy|Natalie Fenton about her new book, ''Democratic Delusions, How the Media Hollows out democracy and What We Can Do About It'']]. One of the most spectacular example of the cost of a news desert is the [[w:City of Bell scandal|Scandal of Bell, California]]. Their local newspaper died around 1999. Roughly a decade later the city was nearly bankrupt in spite of having property tax rates among the highest in the nation. An investigation by the ''[[w:Los Angeles Times|Los Angeles Times]]'' documented that the city manager had a compensation package worth $1.5 million a year, well over double that of the President of the United States. Other senior city officials were similarly well-remunerated. Some of the city officials went to jail over that. Did the city manager decide after 1999, "Wow: The watchdog is dead. Let's have a party"? Malfeasance also increases in business as pollution and workplace accidents increase as does the cost of capital, because investors know their money is not as secure without a local newspaper. That leads to a reduction in investments in new products, services and processes -- slowing economic growth. See "[[Local newspapers limit malfeasance]]", esp. Kim et al. (2021). And executive compensation in increases in nonprofits, so less of what people donate goes to the charitable purpose for which they donated, according to Felix et al. (2024). Also, voter participation and split-ticket voting decline, per Benton (2019) and other references discussed in "[[Information is a public good: Designing experiments to improve government]]". And the ultra-right does better, as noted in [[News from Germany 1900-1945 and implications for today]] and the section on "[[Information is a public good: Designing experiments to improve government#Previous research|Previous research]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]".<ref>Flößer (2024).</ref> The 0.13 percent of GDP savings estimated by Gao et al. (2018) is roughly $120 per human per year. With over 300 million humans in the U.S, that is roughly $40 billion nationwide. {| class="wikitable" |+ Table 1. Costs increase in news deserts |- ! Entity !! What !!Source |- | local government || costs incr. 0.13% of GDP || Gao et al. (2018) |- | local businesses || pollution & workplace accidents incr., innovation & econ growth decr. || Kim et al. (2021) |- | nonprofits || exec. compensation incr. || Felix et al. (2024) |- | rowspan=2 | elections | voter participation & split-ticket voting decl. || Benton (2019) |- | Ultra-right does better || Flößer (2024) |} === Government subsidies for news === John (1995) documented how in the first half of the nineteenth century the US had more independent newspaper publishers per million population than at any other time or place in human history.<ref>This is discussed in the 2025-06-08 [[Media concentration per Columbia History Professor Richard John|interview with him]], available on Wikiversity under [[:Category:Media reform to improve democracy]], accessed 2026-04-30.</ref> This encouraged literacy and limited political corruption, both of which helped [[The Great American Paradox|the early United States stay together and grow]] while contemporary [[w:New Spain|New Spain]] / [[w:Mexico|Mexico]], fractured, shrank, and stagnated economically. As documented with Figure 1 in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]], that growth catapulted the young United States into its current position of dominance in the international political economy, a position it has been losing since at least 1990 -- or since the Reagan Revolution began in 1981, according to the analysis in the chapter below on [[/Fox, the Great Depression, the Great Recession, and our future/]]. Other countries now have stronger democracies due in part to government subsidies for media in the range of 0.05 and 0.25 percent of GDP with a firewall that limits political interference in the content, according to Neff and Pickard (2024). Table 1 in "[[Information is a public good: Designing experiments to improve government]] compares media subsidies in various places with "other points of reference". McChesney and Nichols (2010, pp. 310-311, note 88) suggested that the relatively high rate of economic growth of the economy in the early US was due in part to postal subsidies under the US [[w:Postal Service Act|Postal Service Act]] of 1792.<ref>See also the Wikiversity article on "[[The Great American Paradox]]", accessed 2026-04-30.</ref> They estimated those subsidies at 0.21 percent of GDP. To improve the current political economy of the US, they recommended subsidies of 0.15 percent of GDP distributed to local news nonprofits on the basis of local elections.<ref>McChesney and Nichols (2021, 2022).</ref> The Wikipedia article on "[[Information is a public good: Designing experiments to improve government]]" documents how some jurisdictions can devote that much money to local news nonprofits by matching what they spend on accounting, advertising, and public relations.<ref>See the section on "[[Information is a public good: Designing experiments to improve government#Sampling units / experimental polities|Sampling units / experimental polities]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]", accessed 2026-04-30.</ref> Pickard (2023) describes three basic strategies for confronting concentrated commercial media power: (1) break them up, (2) regulate them, and (3) create non-commercial, public alternatives. A fourth possibility might be [[w:externality|a graduated tax on income and wealth]] in proportion to the threat that major corporations pose to democracy. One class of noncommercial alternatives that Pickard mentions is local multimedia / Public Media Centers (PMCs) with management split between local journalists and boards, e.g., selected at random from registered voters. A key here is to have the boards selected in a way that cannot be influenced by people with power, whether business or political elites. Picard recommends considering '''six discrete layers''' when discussing PMCs, each of which, he says, must be radically democratised: # funding, # governance, # ascertainment (to determine a community’s ''critical information needs''), # infrastructure (including universal broadband service), # algorithmic (e.g., not allowing companies like Google and Facebook to suppress indexing information the might challenge their hegemony of those markets, [[w:Deep web|treating them like pedophilia and the Islamic State]]), # engagement, involving local communities in making their own news and in communicating their own stories; this is paramount to building trust and the grassroots-level support that this new local journalistic model requires. All this needs to be managed in ways that provide substantive support to news deserts and underserved communities that have long been subjected to various kinds of informational redlining. This might be done by including the proposed PMCs within local libraries staffed by professional journalists, who provide training in media literacy in local schools for children and supervise students producing school newspapers. PMCs could host regular, e.g., monthly events, where local residents could share their concerns with journalist, who would use that input to help prioritize different issues for news coverage. Journalist could also coach local residents in how to research issues and collaborate with journalists in producing news reports that may be better researched and more relevant to local concerns than could be produced without such collaboration. Management of such PMCs might be split between journalists on staff and boards of, e.g., six members selected at random from voter registration rolls serving staggered terms of one year with a new member rotated in every 2 months. Another alternative that could be done in parallel with local PMCs calls for 200 journalists in each US Congressional district funded at $10 billion annually in 2022 dollars, which is just a little under 4 hundredths of one percent of GDP; if such allocations are expressed as fractions of a percent of GDP, they would grow naturally with the economy. (The nominal GDP for the US was roughly $26.1 trillion in 2022.<ref>Johnston and Williamson (2026).</ref> For 2026 it is estimated at $32.4 trillion.<ref>[[w:United States|United States]], accessed 2026-04-30.</ref>) A similar model is the [[w:BBC|BBC]]’s Local Democracy Reporting Service (LDRS), in which the BBC funds journalists to cover the work of local councils and other local public bodies, funded at £8 million per year, which is a little under 2 hundredths of a percent of the [[w:United Kingdom|UK]]'s GDP of £7.27 trillion.<ref>[[w:United Kingdom|United Kingdom]], accessed 2026-04-30.</ref> Pickard (2023) ended by saying, "Today we face a crossroads: technocracy and oligarchy from above or radical democracy and structural reform from below. ... [T]his is not just a journalism crisis: it is a democracy crisis." ==Table of Contents== *[[/Introduction/]] including an exercise, asking all to discuss perceptions of the settlement of ''[[w:Dominion Voting Systems v. Fox News Network|Dominion Voting Systems v. Fox News Network]]'' in a friendly supportive manner with humans with whom they may vehemently disagree, because the alternative could be killing humans over misunderstandings. ===Part I. The media and political economy=== # [[/The impact of the media on political economy since the time of the Pharaohs/]] describes how religious leaders in hierarchical societies prior to [[w:James VI and I|King James of the King James bible]] convinced commoners to live in poverty while giving increasing shares of what they produced so religious and secular elites could live in opulence. During the reign of King James, pamphlets and newspapers began to compete with the church for helping commoners understand their roles in society. This produced the Industrial Revolution and modern democracies. Media consolidation since World War II slowed, then reversed this trend. # [[/Fox, the Great Depression, the Great Recession, and our future/]] describes the unprecedented performance of the US political economy during the presidency of Franklin Roosevelt (FDR), insisting that much of what FDR achieved can be replicated, giving a media system that supports honest discussion of the available evidence. # [[/Media consolidation, social media, and political polarization/]] (Combine from McChesney and Nichols discussing the [[w:Postal Service Act|US Postal Service Act]] of 1792 with [[Media concentration per Columbia History Professor Richard John]], the section on "[[v:Information is a public good: Designing experiments to improve government#Threats from social media|Threats from social media]]" in "[[Information is a public good: Designing experiments to improve government]], and the comments by [[v:Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen that, "the shortest path to a click is anger or hate."]]. ===Part II. The media and war=== # [[/Deterrence without threat/]]: The historical record is clear: Nations that have prepared for war often got war, not peace. This happens for at least two reasons: First, some leaders cannot resist the temptation to use force inappropriately, sometimes clandestinely provoking others to do things that are then denounced as "unprovoked"; sometimes the media environment pushes them to do such. Alternatively, potential adversaries may believe -- or claim -- that you are actually preparing a first strike, and they must move preemptively or lose their ability to retaliate adequately. We can avoid these possibilities with three supportive policies: [a] Legislation that ''prohibits'' projecting force beyond our own borders. [b] Civilian-based defense training in nonviolent noncooperation like what helped Denmark survive Nazi occupation with minimal damage. And [c] a media system that penalizes rather than encourages a bellicose foreign policy. # [[/Responding to a nuclear attack/]]: The ''worst'' response to a nuclear attack would be a nuclear response: The death toll from the 1945 [[w:Atomic bombings of Hiroshima and Nagasaki|Atomic bombings of Hiroshima and Nagasaki]] was estimated at between 150,000 and a quarter of a million. By contrast, simulations of nuclear wars of different magnitudes estimated that between 4 and 95 percent of humanity around the world would starve to death if they did not die of something else sooner. The range depends on whether the war was "limited", e.g., between India and Pakistan, and massive between the US and Russia. (Also add material from [[Nuclear weapons and effective defense]]). # [[/Threats from excessive government secrecy/]] (draft in [https://sanjosepeace.org/restrict-secrecy-more-than-data-collection/ "Restrict secrecy more than data collection"], adding material from [https://kkfi.org/program-episodes/does-us-government-secrecy-threaten-national-security/ Connelly (2023) ''The Declassification Engine: What History Reveals About America's Top Secrets''], [[Wikipedia:Moynihan Commission on Government Secrecy]] and [[1998 Embassy bombings and September 11]]. # [[/Shouting fire in a crowded theater/|Shouting ''fire'' in a crowded theater]]: Legal concerns about "[[w:Shouting fire in a crowded theater|Shouting ''fire'' in a crowded theater]]" date, at least in large part, from the [[w:Supreme Court of the United States|US Supreme Court]] decisions in ''[[w:Schenck v. United States|Schenck v. United States]]'' (1919) and ''[[w: Brandenburg v. Ohio| Brandenburg v. Ohio]]'' (1969). In ''Schenck'' the Court ruled that the government had a right to imprison Schenck and others, because their distribution of fliers encouraging draft resistance presented a [[w:clear and present danger|clear and present danger]] to the efficacy of ongoing military activities during [[w:World War I|World War I]], then in progress. The Court in ''Brandenburg'' held that the government cannot punish inflammatory speech ''unless that speech is "directed to inciting or producing imminent lawless action and is likely to incite or produce such action".'' Some could argue that many uses of military force by the US and Israel since 1948 have violated international law, encouraged by biases in the major US media "directed to inciting or producing imminent lawless action", though it may not be feasible to convince a court of that. Still, it might be useful to simulate such a case in a mock trial like the 1966 [[w:Russell Tribunal|Russell Tribunal]].<ref>Andersen (2006) provides such documentation for several such uses of force. Johnson (2026) ''How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza'' organizes evidence supporting such claims for the current [[w:Gaza war|Gaza war]], which began with [[w:October 7 attacks|Palestinian attacks 2023-10-07]]. See also Andersen (2026). Might, e.g., Palestinians -- or at least Palestinian Americans -- be able to sue the [[w:Anti-Defamation League|Anti-Defamation League]] (ADL), the [[w:AIPAC|American Israel Public Affairs Committee]] (AIPAC), and all the major media outlets in the US for inciting genocide in the current [[w:Gaza war|Gaza war]]? That history includes routine suppression of coverage by the major media especially in the US of routine denial of equal protection of Israeli laws to non-Jews in Israel and under Israeli occupation, including suppression of Israeli violence against nonviolent protestors peaceably assembling and petitioning for a redress of grievances combined with over reporting of Palestinian violence and unquestioning coverage of fraudulent claims of Palestinian violence by Israel and supporters. The suppressions included underreporting of Palestinian nonviolence such as the [[w:2018–2019 Gaza border protests|(2018-2019) Great March of Return]], and suppression of the grievances inspiring such nonviolence such as indefinite detention without charges of thousands of Palestinians, including children, routine destruction of Palestinian property by settlers, confiscation of Palestinian property at gunpoint, closing [[w:Gaza Strip|Gaza]] to international trade, and maintaining Gaza on starvation rations. These routine biases in reporting have been encouraged by charges that more honest reporting would be "[[w:Antisemitism|antisemetic]], according to the ADL and AIPAC. This denial of coverage thereby encouraged Israel to increase the rate of such violations until the [[w:October 7 attacks|2023-10-07 attacks on Israel from Gaza]] unleashed Israeli "retaliations" way out of proportion to the alleged provocation. Sucharov (2022) reported that 69% of American Jews opposed privileging Jews over non-Jews in Israel. Their support of Israel in the current Gaza war is consistent with the media biases documented by Johnson (2026) and others including Andersen (2006, 2026). Regarding whether Israel could achieve anything positive from this war, Samuelson (2025) is skeptical. He summarized quantitative analyses of 60 previous insurgencies. The results including the observation that it is exceedingly difficult to defeat an insurgency without responding to the grievances that support it without force ratios far beyond Israel's resources.</ref> ===Part III. Climate, immigrants, education, public health, and criminal justice=== # [[/Global warming/]] [Summarize research especially on conflicts of interest of major media in honestly reporting on this issue and the research on global warming itself and activities of groups concerned about this issue. Decompose into global population times CO2 equivalents per human.] # [[/Immigrants/]] [Summarize research documenting that [[w:Sanctuary city|sanctuary cities tend to have higher median incomes and no more crime than non-sanctuary jurisdictions]], and some studies report less crime. Moreover economists have documented that immigrants tend to be more entrepreneurial, overrepresented in patent applications, and generally increasing the rate of economic growth. See, e.g., Aghion et al. (2022) ''The power of creative destruction''; Aghion shared the 2025 Nobel Memorial Prize in Economics with two others.] # [[/Education/]] (draft in [[Invest in children]].) # [[/Public health/]] [Draft in [[UN public health data]] to be revised to be consistent with Bezruchka (2023, 2025).] # [[/Substance abuse and addictive behavior/]] (Research cited in "[[Wikipedia:War on drugs]]" insists that the US and the world would have fewer problems with substance abuse and addiction problems with 100 percent public funding for treatment programs and complete decriminalization of possession and use of retail quantities of addictive substances. We would also likely have fewer problems with immigrants, as that would make it harder for the US to intervene in the internal affairs of foreign countries funded off the books, as exposed in the [[w:Iran–Contra affair|Iran–Contra affair]]. See [[w:Alfred W. McCoy|Alfred W. McCoy]] (1972; 3rd ed. 2003) ''The politics of heroin''. Journalist [[w:Gary Webb|Gary Webb]] published similar claims that the US intervention in Nicaragua in the Iran-Contra Affair was funded in part by drug money. The story was officially retracted by the ''San José Mercury News'', and Webb allegedly killed himself with 2 bullets to the head. # [[/Criminal justice/]] (Within the range range of experience in the US political economy since 1925, the incarceration rate is uncorrelated with crime: It's a function of the public's perception of crime, and that's a function of the media. That suggest that the US would be safer and more prosperous if incarceration policies were driving more by research than by editorial policies of the media.) # [[/Empower women and girls/]] [Cite research claiming that a primary restraint on population growth is empowering women and girls. Empowering women and girls is not just a matter of equity: It is also a means to reduce the threats of global warming, of increasing exposure to animal diseases and other problems that come with unrestrained population growth.] === Continuation === * [[/The evolving media literacy movement/]] to invite others to keep this book current with the evolving understanding of media literacy, how to encourage and promote it and the benefits of doing so. ==See also== * [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools]] ==Notes== {{reflist}} ==Bibliography== * <!--Daron Acemoğlu and Simon Johnson (2023) Power and Progress-->{{cite Q|Q125292212}} * <!--Robin Andersen (2006) A century of media, a century of war-->{{cite Q|Q138795568}} * <!--Robin Andersen (2026-06-02) The Complicit Lens: US Media Coverage of Israel’s Genocide in Gaza-->{{cite Q|Q138796307}} * <!--Perry Bacon Jr. (2022-10-17) "America Should Spend Billions to Revive Local News"-->{{cite Q|Q139594786}} * <!-- Joshua Benton (9 April 2019). "When local newspapers shrink, fewer people bother to run for mayor". Nieman Foundation for Journalism -->{{cite Q|Q63127216}} * <!--Stephen Bezruchka (2023) Inequality Kills Us All-->{{cite Q|Q136047815}} * <!--Stephen Bezruchka (2025) ''Born Sick in the USA''-->{{cite Q|Q138749292}} * <!--Renée DiResta (2024) Invisible Rulers: The People Who Turn Lies into Reality-->{{cite Q|Q135107164}} * <!--Robert Felix, Joshua A. Khavis, and Mikhail Pevzner (2024) "The effects of local newspaper closures on nonprofits’ executive compensation"-->{{cite Q|Q132730972}} * <!--Maxim Flößer (2024-03-06) "Keine Lokalzeitung -- mehr AfD", Kontext-->{{cite Q|Q125287792}} * <!--Pengjie Gao, Chang Lee, and Dermot Murphy (2018) "Financing Dies in Darkness? The Impact of Newspaper Closures on Public Finance"-->{{cite Q|Q55670016}} * <!--Spencer Graves (2024) "Wikipedia: The most democratic force on earth-->{{cite Q|Q137796922}} * <!--Spencer Graves and Bryan Bailey (2025) "We have to talk", blog at PeaceWorksKC.org-->{{cite Q|Q136126262}} * [[d:Q138038060|Dan Hind and Spencer Graves (2025) "Media Reform Coalition challenges anti-democratic media bias in the UK" on Wikiversity]]. * <!--Richard R. John (1995) Spreading the News: The American Postal System from Franklin to Morse-->{{cite Q|Q54641943}} * <!--Adam H. Johnson (2026-04-21) How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza-->{{cite Q|Q140073447}} * <!--Louis Johnston and Samuel H. Williamson, "What Was the U.S. GDP Then?" MeasuringWorth, 2026-->{{cite Q|Q56881105}} * <!-- Min Kim, Derrald Stice, Han Stice, and Roger M. White (2021) "Stop the presses! Or wait, we might need them: Firm responses to local newspaper closures and layoffs"-->{{cite Q|Q132459373}} * <!-- Robert W. McChesney; John Nichols (2010). The Death and Life of American Journalism (Bold Type Books) -->{{cite Q|Q104888067}}. * <!-- Robert W. McChesney; John Nichols (2021). "The Local Journalism Initiative: a proposal to protect and extend democracy". Columbia Journalism Review, 30 November 2021 -->{{cite Q|Q109978060}} * <!-- Robert W. McChesney; John Nichols (2022), To Protect and Extend Democracy, Recreate Local News Media (PDF), FreePress.net (updated 25 January 2022) -->{{cite Q|Q109978337|access-date=2024-06-23}} * <!--Alfred W. McCoy (2003-05-01) The politics of heroin : CIA complicity in the global drug trade : Afghanistan, Southeast Asia, Central America, Colombia-->{{cite Q|Q141317509}} * <!--Neff and Pickard (2024) "Funding Democracy: Public Media and Democratic Health in 33 Countries"-->{{cite Q|Q131468289}} * [[d:Q131398359|Victor Pickard (2020) ''Democracy without journalism? : confronting the misinformation society'' (Oxford U. Pr.)]]. * <!-- Victor Pickard (2023-05-12) "Another Media System is Possible: Ripping Open the Overton Window, from Platforms to Public Broadcasting"-->{{cite Q|Q131398460}} * <!--Doug Samuelson (2025) Assessing Israel’s Approach in Gaza-->{{cite Q|Q138843324}} * [[d:Q138037937|Dean Starkman and Spencer Graves (2025) "Dean Starkman and the watchdog that didn't bark anglais" on Wikiversity]]. * <!--Mira Sucharov (2022) Do American Jews Really Know What 'Zionist' Means?-->{{cite Q|Q125903777}} * [[d:Q134715465|Nikki Usher and Sanghoon Kim-Leffingwell (2022) "How Loud Does the Watchdog Bark? A Reconsideration of Local Journalism, News Non-profits, and Political Corruption", ''SSRN Electronic Journal'']]. * [[d:Q61013892|Horacio Verbitsky (1997) ''Un mundo sin periodistas'' (in Spanish: A world without journalists; Editorial Sudamericana)]]. [[Category:Communication]] [[Category:Political science]] [[Category:Law]] [[Category:Psychology]] [[Category:Sociology]] [[Category:Education]] [[Category:Economics]] [[Category:Media Literacy and You]] [[Category:Freedom and abundance]] <!-- https://en.wikiversity.org/wiki/Category_Review --> bnjyosf4k0333pywvwk2bqtkt66h9jo 2835348 2835347 2026-10-01T14:10:41Z DavidMCEddy 218607 /* Text and self-help book and point of discuss */ wdsmth 2835348 wikitext text/x-wiki [[File:Pharoah - James VI and I - Trump.png|thumb|Religious and media leaders from the time of the Pharaohs convinced common folk to give increasing shares of what they produced to elites.]] :''This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.'' == Invitation to edit this book == You, dear reader, are invited to contribute questions, ideas and citations to support or refute claims made in this book possibly adding chapters. Wikiversity like other Wikimedia Foundation Projects invites humans to [[w:Wikipedia:Be bold|“be bold but not reckless,”]] while writing from a [[Wikiversity:Disclosures|neutral point of view]], [[Wikiversity:Cite sources|citing credible sources]]. Others are invited to change or revert what you wrote. What stays tends to be written from a neutral point of view citing credible sources. If someone reverts your edit or you have a question, take it to the ''[[Wikiversity:FAQ|''''“Discuss”'''' page]]'' associated with the specific Wikiversity page most related to your concerns. Those who teach media literacy are encouraged to invite their students to debate and revise the contents of this book. Doing so would build on a tradition of [[:w:Wikipedia:Student assignments|instructors requiring students to edit wikipedia article(s).]] Editing [[:w:Wikipedia|Wikipedia]] and other [[:w:Wikimedia Foundation|Wikimedia Foundation]] projects like this book is itself an exercise in media literacy: :''Central tenets of media literacy might include writing from a neutral point of view citing credible sources and engaging others, some of whom may disagree, in civil, supportive conversations about what can and cannot be said based on a reasonable evaluation of the available evidence. Wikimedia rules invite contributors to do just that, encouraging them to “be bold but not reckless,” contributing revisions written from a neutral point of view, citing credible sources -- and raising other questions and concerns on the ''''“Discuss”'''' page associated with the specific Wikiversity page most related to your concerns, as mentioned above.''<ref>For more on this, see Graves (2024).</ref> == Text and self-help book and point of discuss == This book is intended both as a text and self-help book and as a point of discussion considering four levels of media literacy: :1. '''Think before you share''': Follow the money. Every media organization sells changes in audience behaviors to those who control much of their money. [[Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen said]], "The shortest path to a click is anger or hate." The social psychology behind this phenomenon exploited also by legacy media has contributed to [[Media Literacy and You/Media consolidation, social media, and political polarization|the dramatic increase in political polarization and violence worldwide]], especially since the end of the [[w:Fairness doctrine|Fairness doctrine]] in 1987. To counter this, DiResta (2024, p. 335) recommends, "Think before you share." :2. '''Look for information to contradict preconceptions''' (Disconfirmation bias): [[w:Information is a public good: Designing experiments to improve government#Previous research|Virtually everyone]] (a) thinks they know more than they do ([[w:Overconfidence effect|overconfidence effect]]), and (b) prefers information and sources consistent with preconceptions ([[w:Confirmation bias|confirmation bias]]). The major media everywhere exploit this to please those who control most of the money for the media. Humans can counter this by searching for sources to help us understand our designated enemies. If we cannot explain circumstances under which we could see ourselves doing what we see our designated enemies doing, we haven't looked hard enough. :3. '''Talk''': Push ourselves to have friendly supportive conversations with others with whom we may vehemently disagree seeking common ground, agreeing to disagree agreeably where we differ, and building collaboration on areas of common concern.<ref>Graves and Bailey (2025).</ref> :4. '''Teach''': Humans who develop skills in the first three levels can leverage that knowledge in helping others acquire those skills. If each one teaches two<ref>"[[:w:Each one teach one|Each one teach one]]" is an African-American proverb from the time of legalized slavery. However, if each one teaches only one, the growth in literacy will only be linear. Having "each one teaching two", on average, unleashes the power of doubling and [[:w:exponential growth|exponential growth]], which has the potential of educating the entirety of humanity in a reasonable period of time -- namely after 33 doublings starting from one.</ref> in a certain period of time, that time period becomes a [[:w:Doubling time|doubling time]]. Ten doublings is a thousand -- actually 1,024 to be precise.<ref>2 time 2 = 4 times 2 = 8 times 2 = 16 times 2 = 32 times 2 = 64 times 2 = 128 times 2 = 256 times 2 = 512 times 2 = 1024: That's 10 doublings, as anyone with a modest understanding of modern digital [[:w:computer|computer]]s will tell you.</ref> Twenty doublings become a million. Thirty doublings become a billion. Three more doublings become 8 billion, the [[:w:World population|world population]] as of approximately 2022-11-15.<ref>This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.</ref> Many organizations, including several United Nations agencies, already have active [[w:media literacy|media literacy]] programs that have already trained many.<ref>''[[Wikibooks:Antiracist Activism for Teachers and Students]]'' includes a chapter on [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools|Media Literacy In Schools]].</ref> This book is being written hoping to increase the effectiveness and accelerate the rate of growth in media literacy and thereby accelerate progress against many of the most pressing issues facing humanity today. Much of this book is a [[w:Monograph|research monograph]] summarizing research that seems to have been underreported by the major media to avoid offending people who control most of the money for the media. These research results seem to be central to major political divisions. Each chapter ends in exercises to help the reader practice media literacy skills and have fun doing it. Remember: :''I am entitled to my [[Wiktionary:cockamamie|cockamamie]] ideas, and you are entitled to yours.'' Humor is important but must be offered in a way that does not offend others. If others are offended, they may be less interested in dialogue. The term "cockamamie" is used here, hoping that this style of [[w:Self-deprecation|self-deprecation]] might be more inviting for dialogue. ''Never say, "You're wrong." Instead, ask, "May I offer a contrary perspective?" Or "May I share with you another view that I've heard?"'' Much of the information in this book seems to have been largely overlooked and perhaps suppressed, apparently because it would either offend people who control substantial portions of the money for the media our would increase the cost of producing news; see the brief discussion of conflicts of interest by the major media in the next "Key claims" section. ==Key claims== * ''Primary drivers of every major conflict include differences between the media or difference in interpretation that the different parties find credible''. :-- This works, because everything we think we know is coded in systems of connections between neurons in our brains. These systems are more unique than fingerprints and evolve over time. The words we use do not mean the same to two different humans nor even to the same human at different points in time. In many cases these differences are inconsequential. ''Sometimes they are fatal.''<ref>Graves and Bailey (2026).</ref> :-- ''[[w:Social constructionism|Show me someone who knows the truth]], and I will show you someone who is dangerous'' -- especially during war or any other situation where humans may be moved to violence mandated by their belief system.<ref>[[w:Collateral damage|Collateral damage]] that "they" commit proves to "us" that "they" are subhuman or at best criminally misled and must be resisted by any means necessary. By contrast, collateral damage that "we" commit is unfortunate but necessary.</ref> * The major media everywhere have [[w:Conflict of interest|conflicts of interest ]] in honestly reporting on [[v:Information is a public good per communications prof Pickard|anything that might offend anyone who controls large portions of the money for the media]].<ref>Pickard and Graves (2025), accessed 2026-02-08; Pickard (2020).</ref> [[v:Media Reform Coalition challenges anti-democratic media bias in the UK|British journalist and media reform advocate Dan Hind]] said that the content produced by the [[w:BBC|BBC]] was frivolous, soap opera stuff, because leading media personalities know very little about issues of substance and believe "they might get in trouble if" they produced anything serious. Similar analyses seem to apply to the major media everywhere<ref>Hind and Graves (2025), accessed 2026-02-09.</ref> but may not apply to non-profit and local media, which seem more likely to produce [[w:Investigative journalism|investigative]] / [[v:Dean Starkman and the watchdog that didn't bark|accountability journalism]]:<ref>Usher and Kim-Leffingwell (2022); see also Starkman and Graves (2025), accessed 2026-02-09.</ref> [[w:Watchdog journalism|Watchdogs]] tend to protect the people who feed them. Argentine journalist [[w:Horacio Verbitsky|Horacio Verbitsky]] said, "Journalism is disseminating information that someone does not want known; the rest is [[w:propaganda|propaganda]]."<ref>p. 16 in Verbitsky (1997); English translation from [[Wikiquote:Horacio Verbitsky]], accessed 2026-02-09.</ref> * The major media everywhere create the stage upon which politicians read their lines. :-- Their selection of acceptable topics for news and entertainment create and maintain the "[[w:Overton window|Overton window]]", which is the range of acceptable political discourse. For example, in early 1964, US President [[w:Lyndon B. Johnson|Lyndon Johnson]] understood that he could lose the 1964 presidential election that year if he were seen to be soft on communism. His response was to clandestinely provoke an attack on US naval vessels in the Gulf of Tonkin, which he could then denounce as "unprovoked". During a dark and stormy night 1964-08-04 the [[w:USS Maddox (DD-731)|USS ''Maddox'']] and [[w:USS Turner Joy|''Turner Joy'']] spent a couple of hours "defending themselves" against radar snow, then [[w:Gulf of Tonkin incident|reported that they had sunk two attacking North Vietnamese torpedo boats]]; subsequent investigations found no evidence of the reported attacks. That incident was used to justify the [[w:Gulf of Tonkin Resolution|Gulf of Tonkin Resolution]], with only two dissenting votes in the US Congress: Those two dissenters were defeated in their next reelection campaigns, illustrating the point that the major media create the environment in which many politicians cannot get elected without betraying the nation. :-- Nick Hart,<ref name=Hart><!--Nick Hart-->{{cite Q|Q135663983}}</ref> President and CEO of the Data Foundation,<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> noted that President Trump in his first term signed the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]], which was bipartisan legislation ostensibly mandating evidence-informed public policy.<ref>Hart mentioned the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] when he was interviewed for [[Evidence-informed public policy|"Media & Democracy" 2025-07-31]].</ref> The evidence is clear: ::''The US Congress is effectively not allowed to consider solid research suppressed by the major media.'' * The development of technology is never neutral in its impact on inequality but is driven to benefit people with power.<ref>Acemoglu and Johnson (2023)</ref>. :-- [[Media Literacy and You/The impact of the media on political economy since the time of the Pharaohs|Improvements in agricultural technology from pre-history to the time of King James of the King James bible were managed to benefit elites.]] Then pamphlets and newspapers began to appear, the head of state stopped granting as many monopolies, and commoners began getting permission to become entrepreneurs. That transformed economic stagnation into growth in GDP per capita adjusted for inflation, initiating the [[w:Industrial Revolution|Industrial Revolution]], as documented in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]]. It also led to increasing inequality until organized labor got enough political power to demand and get a bigger share of the fruits of their labors. :--[[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|In the US those benefits peaked during the Great Depression]], when the standard conservative mantra that blames the poor for their poverty did not sell newspapers. US President Franklin Roosevelt taxed the ultra-wealthy like they had never been taxed before or since, and dramatically reduced inequality, which continued to decline until increasing concentration of ownership of the media ushered in a new era of increasing inequality starting with the presidency of Ronald Reagan. :-- [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future#Role of the media|Acemoglu and Johnson insist that technology, including artificial intelligence, can be developed to benefit all. However, but it will not happen without action by the poor and middle class as follows]]: :# Alter the narrative, :# Build countervailing powers [like organized labor], and :# Develop technical, regulatory, and policy solutions to tackle specific aspects of technology’s social bias.<ref>Acemoglu and Johnson (2023, ch. 11).</ref> :-- For more on this, see, e.g., the chapter on [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|Fox, the Great Depression, the Great Recession, and our future]]. === The value of noncommercial news outlets === Some of the problems with the media and their contributions to increasing political polarization and violence are documented in the research summary on "[[Information is a public good: Designing experiments to improve government]]" and in the podcast series available on Wikiversity under "[[:Category:Media reform to improve democracy]]" with leading experts discussing their recommendations. One of the most compelling of the references discussed in that podcast series is Usher and Kim-Leffingwell (2022), who tallied all the federal prosecutions for political corruption in each of the 94 [[w:United States federal judicial district|US federal court district]]s between 2003 and 2019. During that period, the number of journalists in the US fell by a factor of roughly 3 -- between 60 and 70 percent. They found no statistically significant impact on federal prosecutions for political corruption of that decline in the number of journalists. However, each member of the [[w:Institute for Nonprofit News|Institute for Nonprofit News]] (INN) in a federal court district in one year was associated with on average 1.4 additional prosecutions for political corruption the following year. Since federal prosecutions for political corruption averaged roughly 10 per federal court district per year during that period. each member of INN in a federal court district one year was associated with a 14 percent increase in federal prosecutions the following year. This suggests that the major media outlets that had so dramatically reduced their staffs had not substantively reduced the amount of investigative journalism they did. If we assume that the people prosecuted for political corruption also control substantive advertising budgets, then the major media outlets have conflicts of interest in honestly reporting on such. They may report on it if some other organization like a member of INN does the research and they are threatened with a loss of audience from not reporting on it. :'''''Major point''''': You and I benefit, the vast majority of humans on earth benefit, from news reports presumably published by members of INN that contributed to those on average 1.4 additional prosecutions for political corruption estimated by Usher and Kim-Leffingwell (2022). We benefit even if we never heard about the news reports that contributed to those prosecutions. We benefit even if we have never heard of the news outlets that presumably did the investigative journalism behind those additional prosecutions. Why? Because on average those news reports likely deterred other incidents of political corruption, which likely contributed to broadly shared economic growth and the development of new technology that ultimately benefit the vast majority of humanity. Other aspects of this are documented in the research on the impact of [[w:news desert|news desert]]s, which we summarize next. === Costs increase in news deserts=== There's a growing body of research describing what happens when local newspapers die. Perhaps most important, a 2018 research report by Gao et al. reported that the death of a local newspaper was followed by … increases in local tax revenue, averaging $85 per human per year.<ref name = Gao2018>Gao et al. (2018).</ref> That $85 was roughly 13 hundredths of a percent of the 2019 US GDP. That's mentioned in the 2025-07-17 interview with [[Democratic delusions: Fix the media to fix democracy|Natalie Fenton about her new book, ''Democratic Delusions, How the Media Hollows out democracy and What We Can Do About It'']]. One of the most spectacular example of the cost of a news desert is the [[w:City of Bell scandal|Scandal of Bell, California]]. Their local newspaper died around 1999. Roughly a decade later the city was nearly bankrupt in spite of having property tax rates among the highest in the nation. An investigation by the ''[[w:Los Angeles Times|Los Angeles Times]]'' documented that the city manager had a compensation package worth $1.5 million a year, well over double that of the President of the United States. Other senior city officials were similarly well-remunerated. Some of the city officials went to jail over that. Did the city manager decide after 1999, "Wow: The watchdog is dead. Let's have a party"? Malfeasance also increases in business as pollution and workplace accidents increase as does the cost of capital, because investors know their money is not as secure without a local newspaper. That leads to a reduction in investments in new products, services and processes -- slowing economic growth. See "[[Local newspapers limit malfeasance]]", esp. Kim et al. (2021). And executive compensation in increases in nonprofits, so less of what people donate goes to the charitable purpose for which they donated, according to Felix et al. (2024). Also, voter participation and split-ticket voting decline, per Benton (2019) and other references discussed in "[[Information is a public good: Designing experiments to improve government]]". And the ultra-right does better, as noted in [[News from Germany 1900-1945 and implications for today]] and the section on "[[Information is a public good: Designing experiments to improve government#Previous research|Previous research]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]".<ref>Flößer (2024).</ref> The 0.13 percent of GDP savings estimated by Gao et al. (2018) is roughly $120 per human per year. With over 300 million humans in the U.S, that is roughly $40 billion nationwide. {| class="wikitable" |+ Table 1. Costs increase in news deserts |- ! Entity !! What !!Source |- | local government || costs incr. 0.13% of GDP || Gao et al. (2018) |- | local businesses || pollution & workplace accidents incr., innovation & econ growth decr. || Kim et al. (2021) |- | nonprofits || exec. compensation incr. || Felix et al. (2024) |- | rowspan=2 | elections | voter participation & split-ticket voting decl. || Benton (2019) |- | Ultra-right does better || Flößer (2024) |} === Government subsidies for news === John (1995) documented how in the first half of the nineteenth century the US had more independent newspaper publishers per million population than at any other time or place in human history.<ref>This is discussed in the 2025-06-08 [[Media concentration per Columbia History Professor Richard John|interview with him]], available on Wikiversity under [[:Category:Media reform to improve democracy]], accessed 2026-04-30.</ref> This encouraged literacy and limited political corruption, both of which helped [[The Great American Paradox|the early United States stay together and grow]] while contemporary [[w:New Spain|New Spain]] / [[w:Mexico|Mexico]], fractured, shrank, and stagnated economically. As documented with Figure 1 in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]], that growth catapulted the young United States into its current position of dominance in the international political economy, a position it has been losing since at least 1990 -- or since the Reagan Revolution began in 1981, according to the analysis in the chapter below on [[/Fox, the Great Depression, the Great Recession, and our future/]]. Other countries now have stronger democracies due in part to government subsidies for media in the range of 0.05 and 0.25 percent of GDP with a firewall that limits political interference in the content, according to Neff and Pickard (2024). Table 1 in "[[Information is a public good: Designing experiments to improve government]] compares media subsidies in various places with "other points of reference". McChesney and Nichols (2010, pp. 310-311, note 88) suggested that the relatively high rate of economic growth of the economy in the early US was due in part to postal subsidies under the US [[w:Postal Service Act|Postal Service Act]] of 1792.<ref>See also the Wikiversity article on "[[The Great American Paradox]]", accessed 2026-04-30.</ref> They estimated those subsidies at 0.21 percent of GDP. To improve the current political economy of the US, they recommended subsidies of 0.15 percent of GDP distributed to local news nonprofits on the basis of local elections.<ref>McChesney and Nichols (2021, 2022).</ref> The Wikipedia article on "[[Information is a public good: Designing experiments to improve government]]" documents how some jurisdictions can devote that much money to local news nonprofits by matching what they spend on accounting, advertising, and public relations.<ref>See the section on "[[Information is a public good: Designing experiments to improve government#Sampling units / experimental polities|Sampling units / experimental polities]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]", accessed 2026-04-30.</ref> Pickard (2023) describes three basic strategies for confronting concentrated commercial media power: (1) break them up, (2) regulate them, and (3) create non-commercial, public alternatives. A fourth possibility might be [[w:externality|a graduated tax on income and wealth]] in proportion to the threat that major corporations pose to democracy. One class of noncommercial alternatives that Pickard mentions is local multimedia / Public Media Centers (PMCs) with management split between local journalists and boards, e.g., selected at random from registered voters. A key here is to have the boards selected in a way that cannot be influenced by people with power, whether business or political elites. Picard recommends considering '''six discrete layers''' when discussing PMCs, each of which, he says, must be radically democratised: # funding, # governance, # ascertainment (to determine a community’s ''critical information needs''), # infrastructure (including universal broadband service), # algorithmic (e.g., not allowing companies like Google and Facebook to suppress indexing information the might challenge their hegemony of those markets, [[w:Deep web|treating them like pedophilia and the Islamic State]]), # engagement, involving local communities in making their own news and in communicating their own stories; this is paramount to building trust and the grassroots-level support that this new local journalistic model requires. All this needs to be managed in ways that provide substantive support to news deserts and underserved communities that have long been subjected to various kinds of informational redlining. This might be done by including the proposed PMCs within local libraries staffed by professional journalists, who provide training in media literacy in local schools for children and supervise students producing school newspapers. PMCs could host regular, e.g., monthly events, where local residents could share their concerns with journalist, who would use that input to help prioritize different issues for news coverage. Journalist could also coach local residents in how to research issues and collaborate with journalists in producing news reports that may be better researched and more relevant to local concerns than could be produced without such collaboration. Management of such PMCs might be split between journalists on staff and boards of, e.g., six members selected at random from voter registration rolls serving staggered terms of one year with a new member rotated in every 2 months. Another alternative that could be done in parallel with local PMCs calls for 200 journalists in each US Congressional district funded at $10 billion annually in 2022 dollars, which is just a little under 4 hundredths of one percent of GDP; if such allocations are expressed as fractions of a percent of GDP, they would grow naturally with the economy. (The nominal GDP for the US was roughly $26.1 trillion in 2022.<ref>Johnston and Williamson (2026).</ref> For 2026 it is estimated at $32.4 trillion.<ref>[[w:United States|United States]], accessed 2026-04-30.</ref>) A similar model is the [[w:BBC|BBC]]’s Local Democracy Reporting Service (LDRS), in which the BBC funds journalists to cover the work of local councils and other local public bodies, funded at £8 million per year, which is a little under 2 hundredths of a percent of the [[w:United Kingdom|UK]]'s GDP of £7.27 trillion.<ref>[[w:United Kingdom|United Kingdom]], accessed 2026-04-30.</ref> Pickard (2023) ended by saying, "Today we face a crossroads: technocracy and oligarchy from above or radical democracy and structural reform from below. ... [T]his is not just a journalism crisis: it is a democracy crisis." ==Table of Contents== *[[/Introduction/]] including an exercise, asking all to discuss perceptions of the settlement of ''[[w:Dominion Voting Systems v. Fox News Network|Dominion Voting Systems v. Fox News Network]]'' in a friendly supportive manner with humans with whom they may vehemently disagree, because the alternative could be killing humans over misunderstandings. ===Part I. The media and political economy=== # [[/The impact of the media on political economy since the time of the Pharaohs/]] describes how religious leaders in hierarchical societies prior to [[w:James VI and I|King James of the King James bible]] convinced commoners to live in poverty while giving increasing shares of what they produced so religious and secular elites could live in opulence. During the reign of King James, pamphlets and newspapers began to compete with the church for helping commoners understand their roles in society. This produced the Industrial Revolution and modern democracies. Media consolidation since World War II slowed, then reversed this trend. # [[/Fox, the Great Depression, the Great Recession, and our future/]] describes the unprecedented performance of the US political economy during the presidency of Franklin Roosevelt (FDR), insisting that much of what FDR achieved can be replicated, giving a media system that supports honest discussion of the available evidence. # [[/Media consolidation, social media, and political polarization/]] (Combine from McChesney and Nichols discussing the [[w:Postal Service Act|US Postal Service Act]] of 1792 with [[Media concentration per Columbia History Professor Richard John]], the section on "[[v:Information is a public good: Designing experiments to improve government#Threats from social media|Threats from social media]]" in "[[Information is a public good: Designing experiments to improve government]], and the comments by [[v:Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen that, "the shortest path to a click is anger or hate."]]. ===Part II. The media and war=== # [[/Deterrence without threat/]]: The historical record is clear: Nations that have prepared for war often got war, not peace. This happens for at least two reasons: First, some leaders cannot resist the temptation to use force inappropriately, sometimes clandestinely provoking others to do things that are then denounced as "unprovoked"; sometimes the media environment pushes them to do such. Alternatively, potential adversaries may believe -- or claim -- that you are actually preparing a first strike, and they must move preemptively or lose their ability to retaliate adequately. We can avoid these possibilities with three supportive policies: [a] Legislation that ''prohibits'' projecting force beyond our own borders. [b] Civilian-based defense training in nonviolent noncooperation like what helped Denmark survive Nazi occupation with minimal damage. And [c] a media system that penalizes rather than encourages a bellicose foreign policy. # [[/Responding to a nuclear attack/]]: The ''worst'' response to a nuclear attack would be a nuclear response: The death toll from the 1945 [[w:Atomic bombings of Hiroshima and Nagasaki|Atomic bombings of Hiroshima and Nagasaki]] was estimated at between 150,000 and a quarter of a million. By contrast, simulations of nuclear wars of different magnitudes estimated that between 4 and 95 percent of humanity around the world would starve to death if they did not die of something else sooner. The range depends on whether the war was "limited", e.g., between India and Pakistan, and massive between the US and Russia. (Also add material from [[Nuclear weapons and effective defense]]). # [[/Threats from excessive government secrecy/]] (draft in [https://sanjosepeace.org/restrict-secrecy-more-than-data-collection/ "Restrict secrecy more than data collection"], adding material from [https://kkfi.org/program-episodes/does-us-government-secrecy-threaten-national-security/ Connelly (2023) ''The Declassification Engine: What History Reveals About America's Top Secrets''], [[Wikipedia:Moynihan Commission on Government Secrecy]] and [[1998 Embassy bombings and September 11]]. # [[/Shouting fire in a crowded theater/|Shouting ''fire'' in a crowded theater]]: Legal concerns about "[[w:Shouting fire in a crowded theater|Shouting ''fire'' in a crowded theater]]" date, at least in large part, from the [[w:Supreme Court of the United States|US Supreme Court]] decisions in ''[[w:Schenck v. United States|Schenck v. United States]]'' (1919) and ''[[w: Brandenburg v. Ohio| Brandenburg v. Ohio]]'' (1969). In ''Schenck'' the Court ruled that the government had a right to imprison Schenck and others, because their distribution of fliers encouraging draft resistance presented a [[w:clear and present danger|clear and present danger]] to the efficacy of ongoing military activities during [[w:World War I|World War I]], then in progress. The Court in ''Brandenburg'' held that the government cannot punish inflammatory speech ''unless that speech is "directed to inciting or producing imminent lawless action and is likely to incite or produce such action".'' Some could argue that many uses of military force by the US and Israel since 1948 have violated international law, encouraged by biases in the major US media "directed to inciting or producing imminent lawless action", though it may not be feasible to convince a court of that. Still, it might be useful to simulate such a case in a mock trial like the 1966 [[w:Russell Tribunal|Russell Tribunal]].<ref>Andersen (2006) provides such documentation for several such uses of force. Johnson (2026) ''How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza'' organizes evidence supporting such claims for the current [[w:Gaza war|Gaza war]], which began with [[w:October 7 attacks|Palestinian attacks 2023-10-07]]. See also Andersen (2026). Might, e.g., Palestinians -- or at least Palestinian Americans -- be able to sue the [[w:Anti-Defamation League|Anti-Defamation League]] (ADL), the [[w:AIPAC|American Israel Public Affairs Committee]] (AIPAC), and all the major media outlets in the US for inciting genocide in the current [[w:Gaza war|Gaza war]]? That history includes routine suppression of coverage by the major media especially in the US of routine denial of equal protection of Israeli laws to non-Jews in Israel and under Israeli occupation, including suppression of Israeli violence against nonviolent protestors peaceably assembling and petitioning for a redress of grievances combined with over reporting of Palestinian violence and unquestioning coverage of fraudulent claims of Palestinian violence by Israel and supporters. The suppressions included underreporting of Palestinian nonviolence such as the [[w:2018–2019 Gaza border protests|(2018-2019) Great March of Return]], and suppression of the grievances inspiring such nonviolence such as indefinite detention without charges of thousands of Palestinians, including children, routine destruction of Palestinian property by settlers, confiscation of Palestinian property at gunpoint, closing [[w:Gaza Strip|Gaza]] to international trade, and maintaining Gaza on starvation rations. These routine biases in reporting have been encouraged by charges that more honest reporting would be "[[w:Antisemitism|antisemetic]], according to the ADL and AIPAC. This denial of coverage thereby encouraged Israel to increase the rate of such violations until the [[w:October 7 attacks|2023-10-07 attacks on Israel from Gaza]] unleashed Israeli "retaliations" way out of proportion to the alleged provocation. Sucharov (2022) reported that 69% of American Jews opposed privileging Jews over non-Jews in Israel. Their support of Israel in the current Gaza war is consistent with the media biases documented by Johnson (2026) and others including Andersen (2006, 2026). Regarding whether Israel could achieve anything positive from this war, Samuelson (2025) is skeptical. He summarized quantitative analyses of 60 previous insurgencies. The results including the observation that it is exceedingly difficult to defeat an insurgency without responding to the grievances that support it without force ratios far beyond Israel's resources.</ref> ===Part III. Climate, immigrants, education, public health, and criminal justice=== # [[/Global warming/]] [Summarize research especially on conflicts of interest of major media in honestly reporting on this issue and the research on global warming itself and activities of groups concerned about this issue. Decompose into global population times CO2 equivalents per human.] # [[/Immigrants/]] [Summarize research documenting that [[w:Sanctuary city|sanctuary cities tend to have higher median incomes and no more crime than non-sanctuary jurisdictions]], and some studies report less crime. Moreover economists have documented that immigrants tend to be more entrepreneurial, overrepresented in patent applications, and generally increasing the rate of economic growth. See, e.g., Aghion et al. (2022) ''The power of creative destruction''; Aghion shared the 2025 Nobel Memorial Prize in Economics with two others.] # [[/Education/]] (draft in [[Invest in children]].) # [[/Public health/]] [Draft in [[UN public health data]] to be revised to be consistent with Bezruchka (2023, 2025).] # [[/Substance abuse and addictive behavior/]] (Research cited in "[[Wikipedia:War on drugs]]" insists that the US and the world would have fewer problems with substance abuse and addiction problems with 100 percent public funding for treatment programs and complete decriminalization of possession and use of retail quantities of addictive substances. We would also likely have fewer problems with immigrants, as that would make it harder for the US to intervene in the internal affairs of foreign countries funded off the books, as exposed in the [[w:Iran–Contra affair|Iran–Contra affair]]. See [[w:Alfred W. McCoy|Alfred W. McCoy]] (1972; 3rd ed. 2003) ''The politics of heroin''. Journalist [[w:Gary Webb|Gary Webb]] published similar claims that the US intervention in Nicaragua in the Iran-Contra Affair was funded in part by drug money. The story was officially retracted by the ''San José Mercury News'', and Webb allegedly killed himself with 2 bullets to the head. # [[/Criminal justice/]] (Within the range range of experience in the US political economy since 1925, the incarceration rate is uncorrelated with crime: It's a function of the public's perception of crime, and that's a function of the media. That suggest that the US would be safer and more prosperous if incarceration policies were driving more by research than by editorial policies of the media.) # [[/Empower women and girls/]] [Cite research claiming that a primary restraint on population growth is empowering women and girls. Empowering women and girls is not just a matter of equity: It is also a means to reduce the threats of global warming, of increasing exposure to animal diseases and other problems that come with unrestrained population growth.] === Continuation === * [[/The evolving media literacy movement/]] to invite others to keep this book current with the evolving understanding of media literacy, how to encourage and promote it and the benefits of doing so. ==See also== * [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools]] ==Notes== {{reflist}} ==Bibliography== * <!--Daron Acemoğlu and Simon Johnson (2023) Power and Progress-->{{cite Q|Q125292212}} * <!--Robin Andersen (2006) A century of media, a century of war-->{{cite Q|Q138795568}} * <!--Robin Andersen (2026-06-02) The Complicit Lens: US Media Coverage of Israel’s Genocide in Gaza-->{{cite Q|Q138796307}} * <!--Perry Bacon Jr. (2022-10-17) "America Should Spend Billions to Revive Local News"-->{{cite Q|Q139594786}} * <!-- Joshua Benton (9 April 2019). "When local newspapers shrink, fewer people bother to run for mayor". Nieman Foundation for Journalism -->{{cite Q|Q63127216}} * <!--Stephen Bezruchka (2023) Inequality Kills Us All-->{{cite Q|Q136047815}} * <!--Stephen Bezruchka (2025) ''Born Sick in the USA''-->{{cite Q|Q138749292}} * <!--Renée DiResta (2024) Invisible Rulers: The People Who Turn Lies into Reality-->{{cite Q|Q135107164}} * <!--Robert Felix, Joshua A. Khavis, and Mikhail Pevzner (2024) "The effects of local newspaper closures on nonprofits’ executive compensation"-->{{cite Q|Q132730972}} * <!--Maxim Flößer (2024-03-06) "Keine Lokalzeitung -- mehr AfD", Kontext-->{{cite Q|Q125287792}} * <!--Pengjie Gao, Chang Lee, and Dermot Murphy (2018) "Financing Dies in Darkness? The Impact of Newspaper Closures on Public Finance"-->{{cite Q|Q55670016}} * <!--Spencer Graves (2024) "Wikipedia: The most democratic force on earth-->{{cite Q|Q137796922}} * <!--Spencer Graves and Bryan Bailey (2025) "We have to talk", blog at PeaceWorksKC.org-->{{cite Q|Q136126262}} * [[d:Q138038060|Dan Hind and Spencer Graves (2025) "Media Reform Coalition challenges anti-democratic media bias in the UK" on Wikiversity]]. * <!--Richard R. John (1995) Spreading the News: The American Postal System from Franklin to Morse-->{{cite Q|Q54641943}} * <!--Adam H. Johnson (2026-04-21) How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza-->{{cite Q|Q140073447}} * <!--Louis Johnston and Samuel H. Williamson, "What Was the U.S. GDP Then?" MeasuringWorth, 2026-->{{cite Q|Q56881105}} * <!-- Min Kim, Derrald Stice, Han Stice, and Roger M. White (2021) "Stop the presses! Or wait, we might need them: Firm responses to local newspaper closures and layoffs"-->{{cite Q|Q132459373}} * <!-- Robert W. McChesney; John Nichols (2010). The Death and Life of American Journalism (Bold Type Books) -->{{cite Q|Q104888067}}. * <!-- Robert W. McChesney; John Nichols (2021). "The Local Journalism Initiative: a proposal to protect and extend democracy". Columbia Journalism Review, 30 November 2021 -->{{cite Q|Q109978060}} * <!-- Robert W. McChesney; John Nichols (2022), To Protect and Extend Democracy, Recreate Local News Media (PDF), FreePress.net (updated 25 January 2022) -->{{cite Q|Q109978337|access-date=2024-06-23}} * <!--Alfred W. McCoy (2003-05-01) The politics of heroin : CIA complicity in the global drug trade : Afghanistan, Southeast Asia, Central America, Colombia-->{{cite Q|Q141317509}} * <!--Neff and Pickard (2024) "Funding Democracy: Public Media and Democratic Health in 33 Countries"-->{{cite Q|Q131468289}} * [[d:Q131398359|Victor Pickard (2020) ''Democracy without journalism? : confronting the misinformation society'' (Oxford U. Pr.)]]. * <!-- Victor Pickard (2023-05-12) "Another Media System is Possible: Ripping Open the Overton Window, from Platforms to Public Broadcasting"-->{{cite Q|Q131398460}} * <!--Doug Samuelson (2025) Assessing Israel’s Approach in Gaza-->{{cite Q|Q138843324}} * [[d:Q138037937|Dean Starkman and Spencer Graves (2025) "Dean Starkman and the watchdog that didn't bark anglais" on Wikiversity]]. * <!--Mira Sucharov (2022) Do American Jews Really Know What 'Zionist' Means?-->{{cite Q|Q125903777}} * [[d:Q134715465|Nikki Usher and Sanghoon Kim-Leffingwell (2022) "How Loud Does the Watchdog Bark? A Reconsideration of Local Journalism, News Non-profits, and Political Corruption", ''SSRN Electronic Journal'']]. * [[d:Q61013892|Horacio Verbitsky (1997) ''Un mundo sin periodistas'' (in Spanish: A world without journalists; Editorial Sudamericana)]]. [[Category:Communication]] [[Category:Political science]] [[Category:Law]] [[Category:Psychology]] [[Category:Sociology]] [[Category:Education]] [[Category:Economics]] [[Category:Media Literacy and You]] [[Category:Freedom and abundance]] <!-- https://en.wikiversity.org/wiki/Category_Review --> gnpo2ddvtsnzdtp0p4shwp9qa922aj6 2835349 2835348 2026-10-01T14:40:41Z DavidMCEddy 218607 chk chgs 2835349 wikitext text/x-wiki [[File:Pharoah - James VI and I - Trump.png|thumb|Religious and media leaders from the time of the Pharaohs convinced common folk to give increasing shares of what they produced to elites.]] :''This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.'' == Invitation to edit this book == You, dear reader, are invited to contribute questions, ideas and citations to support or refute claims made in this book possibly adding chapters. Wikiversity like other Wikimedia Foundation Projects invites humans to [[w:Wikipedia:Be bold|“be bold but not reckless,”]] while writing from a [[Wikiversity:Disclosures|neutral point of view]], [[Wikiversity:Cite sources|citing credible sources]]. Others are invited to change or revert what you wrote. What stays tends to be written from a neutral point of view citing credible sources. If someone reverts your edit or you have a question, take it to the ''[[Wikiversity:FAQ|''''“Discuss”'''' page]]'' associated with the specific Wikiversity page most related to your concerns. Those who teach media literacy are encouraged to invite their students to debate and revise the contents of this book. Doing so would build on a tradition of [[:w:Wikipedia:Student assignments|instructors requiring students to edit wikipedia article(s).]] Editing [[:w:Wikipedia|Wikipedia]] and other [[:w:Wikimedia Foundation|Wikimedia Foundation]] projects like this book is itself an exercise in media literacy: :''Central tenets of media literacy might include writing from a neutral point of view citing credible sources and engaging others, some of whom may disagree, in civil, supportive conversations about what can and cannot be said based on a reasonable evaluation of the available evidence. Wikimedia rules invite contributors to do just that, encouraging them to “be bold but not reckless,” contributing revisions written from a neutral point of view, citing credible sources -- and raising other questions and concerns on the ''''“Discuss”'''' page associated with the specific Wikiversity page most related to your concerns, as mentioned above.''<ref>For more on this, see Graves (2024).</ref> == Text and self-help book and point of discuss == This book is intended both as a text and self-help book and as a point of discussion considering four levels of media literacy: :1. '''Think before you share''': [[Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen said]], "The shortest path to a click is anger or hate." The social psychology behind this phenomenon exploited also by legacy media has contributed to [[Media Literacy and You/Media consolidation, social media, and political polarization|the dramatic increase in political polarization and violence worldwide]], especially since the end of the [[w:Fairness doctrine|Fairness doctrine]] in 1987. To counter this, DiResta (2024, p. 335) recommends, "Think before you share." :2. '''Look for information to contradict preconceptions''' (Disconfirmation bias): [[w:Information is a public good: Designing experiments to improve government#Previous research|Virtually everyone]] (a) thinks they know more than they do ([[w:Overconfidence effect|overconfidence effect]]), and (b) prefers information and sources consistent with preconceptions ([[w:Confirmation bias|confirmation bias]]). The major media everywhere exploit this to please those who control most of the money for the media. Humans can counter this by searching for sources to help us understand our designated enemies. If we cannot explain circumstances under which we could see ourselves doing what we see our designated enemies doing, we haven't looked hard enough. :3. '''Talk''': Push ourselves to have friendly supportive conversations with others with whom we may vehemently disagree with the goals of agreeing to disagree agreeably and building collaboration on areas of common concern.<ref>Graves and Bailey (2025).</ref> :4. '''Teach''': Humans who develop skills in the first three levels can leverage that knowledge in helping others acquire those skills. If each one teaches two<ref>"[[:w:Each one teach one|Each one teach one]]" is an African-American proverb from the time of legalized slavery. However, if each one teaches only one, the growth in literacy will only be linear. Having "each one teaching two", on average, unleashes the power of doubling and [[:w:exponential growth|exponential growth]], which has the potential of educating the entirety of humanity in a reasonable period of time -- namely after 33 doublings starting from one.</ref> in a certain period of time, that time period becomes a [[:w:Doubling time|doubling time]]. Ten doublings is a thousand -- actually 1,024 to be precise.<ref>2 time 2 = 4 times 2 = 8 times 2 = 16 times 2 = 32 times 2 = 64 times 2 = 128 times 2 = 256 times 2 = 512 times 2 = 1024: That's 10 doublings, as anyone with a modest understanding of modern digital [[:w:computer|computer]]s will tell you.</ref> Twenty doublings become a million. Thirty doublings become a billion. Three more doublings become 8 billion, the [[:w:World population|world population]] as of approximately 2022-11-15.<ref>This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.</ref> Many organizations, including several United Nations agencies, already have active [[w:media literacy|media literacy]] programs that have already trained many.<ref>''[[Wikibooks:Antiracist Activism for Teachers and Students]]'' includes a chapter on [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools|Media Literacy In Schools]].</ref> This book is being written hoping to increase the effectiveness and accelerate the rate of growth in media literacy and thereby accelerate progress against many of the most pressing issues facing humanity today. Much of this book is a [[w:Monograph|research monograph]] summarizing research that seems to have been underreported by the major media to avoid offending people who control most of the money for the media. These research results seem to be central to major political divisions. Each chapter ends in exercises to help the reader practice media literacy skills and have fun doing it. Remember: :''I am entitled to my [[Wiktionary:cockamamie|cockamamie]] ideas, and you are entitled to yours.'' Humor is important but must be offered in a way that does not offend others. If others are offended, they may be less interested in dialogue. The term "cockamamie" is used here, hoping that this style of [[w:Self-deprecation|self-deprecation]] might be more inviting for dialogue. ''Never say, "You're wrong." Instead, ask, "May I offer a contrary perspective?" Or "May I share with you another view that I've heard?"'' Much of the information in this book seems to have been largely overlooked and perhaps suppressed, apparently because it would either offend people who control substantial portions of the money for the media our would increase the cost of producing news; see the brief discussion of conflicts of interest by the major media in the next "Key claims" section. ==Key claims== * ''Primary drivers of every major conflict include differences between the media or difference in interpretation that the different parties find credible''. :-- This works, because everything we think we know is coded in systems of connections between neurons in our brains. These systems are more unique than fingerprints and evolve over time. The words we use do not mean the same to two different humans nor even to the same human at different points in time. In many cases these differences are inconsequential. ''Sometimes they are fatal.''<ref>Graves and Bailey (2026).</ref> :-- ''[[w:Social constructionism|Show me someone who knows the truth]], and I will show you someone who is dangerous'' -- especially during war or any other situation where humans may be moved to violence mandated by their belief system.<ref>[[w:Collateral damage|Collateral damage]] that "they" commit proves to "us" that "they" are subhuman or at best criminally misled and must be resisted by any means necessary. By contrast, collateral damage that "we" commit is unfortunate but necessary.</ref> * The major media everywhere have [[w:Conflict of interest|conflicts of interest ]] in honestly reporting on [[v:Information is a public good per communications prof Pickard|anything that might offend anyone who controls large portions of the money for the media]].<ref>Pickard and Graves (2025), accessed 2026-02-08; Pickard (2020).</ref> [[v:Media Reform Coalition challenges anti-democratic media bias in the UK|British journalist and media reform advocate Dan Hind]] said that the content produced by the [[w:BBC|BBC]] was frivolous, soap opera stuff, because leading media personalities know very little about issues of substance and believe "they might get in trouble if" they produced anything serious. Similar analyses seem to apply to the major media everywhere<ref>Hind and Graves (2025), accessed 2026-02-09.</ref> but may not apply to non-profit and local media, which seem more likely to produce [[w:Investigative journalism|investigative]] / [[v:Dean Starkman and the watchdog that didn't bark|accountability journalism]]:<ref>Usher and Kim-Leffingwell (2022); see also Starkman and Graves (2025), accessed 2026-02-09.</ref> [[w:Watchdog journalism|Watchdogs]] tend to protect the people who feed them. Argentine journalist [[w:Horacio Verbitsky|Horacio Verbitsky]] said, "Journalism is disseminating information that someone does not want known; the rest is [[w:propaganda|propaganda]]."<ref>p. 16 in Verbitsky (1997); English translation from [[Wikiquote:Horacio Verbitsky]], accessed 2026-02-09.</ref> * The major media everywhere create the stage upon which politicians read their lines. :-- Their selection of acceptable topics for news and entertainment create and maintain the "[[w:Overton window|Overton window]]", which is the range of acceptable political discourse. For example, in early 1964, US President [[w:Lyndon B. Johnson|Lyndon Johnson]] understood that he could lose the 1964 presidential election that year if he were seen to be soft on communism. His response was to clandestinely provoke an attack on US naval vessels in the Gulf of Tonkin, which he could then denounce as "unprovoked". During a dark and stormy night 1964-08-04 the [[w:USS Maddox (DD-731)|USS ''Maddox'']] and [[w:USS Turner Joy|''Turner Joy'']] spent a couple of hours "defending themselves" against radar snow, then [[w:Gulf of Tonkin incident|reported that they had sunk two attacking North Vietnamese torpedo boats]]; subsequent investigations found no evidence of the reported attacks. That incident was used to justify the [[w:Gulf of Tonkin Resolution|Gulf of Tonkin Resolution]], with only two dissenting votes in the US Congress: Those two dissenters were defeated in their next reelection campaigns, illustrating the point that the major media create the environment in which many politicians cannot get elected without betraying the nation. :-- Nick Hart,<ref name=Hart><!--Nick Hart-->{{cite Q|Q135663983}}</ref> President and CEO of the Data Foundation,<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> noted that President Trump in his first term signed the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]], which was bipartisan legislation ostensibly mandating evidence-informed public policy.<ref>Hart mentioned the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] when he was interviewed for [[Evidence-informed public policy|"Media & Democracy" 2025-07-31]].</ref> The evidence is clear: ::''The US Congress is effectively not allowed to consider solid research suppressed by the major media.'' * The development of technology is never neutral in its impact on inequality but is driven to benefit people with power.<ref>Acemoglu and Johnson (2023)</ref>. :-- [[Media Literacy and You/The impact of the media on political economy since the time of the Pharaohs|Improvements in agricultural technology from pre-history to the time of King James of the King James bible were managed to benefit elites.]] Then pamphlets and newspapers began to appear, the head of state stopped granting as many monopolies, and commoners began getting permission to become entrepreneurs. That transformed economic stagnation into growth in GDP per capita adjusted for inflation, initiating the [[w:Industrial Revolution|Industrial Revolution]], as documented in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]]. It also led to increasing inequality until organized labor got enough political power to demand and get a bigger share of the fruits of their labors. :--[[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|In the US those benefits peaked during the Great Depression]], when the standard conservative mantra that blames the poor for their poverty did not sell newspapers. US President Franklin Roosevelt taxed the ultra-wealthy like they had never been taxed before or since, and dramatically reduced inequality, which continued to decline until increasing concentration of ownership of the media ushered in a new era of increasing inequality starting with the presidency of Ronald Reagan. :-- [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future#Role of the media|Acemoglu and Johnson insist that technology, including artificial intelligence, can be developed to benefit all. However, but it will not happen without action by the poor and middle class as follows]]: :# Alter the narrative, :# Build countervailing powers [like organized labor], and :# Develop technical, regulatory, and policy solutions to tackle specific aspects of technology’s social bias.<ref>Acemoglu and Johnson (2023, ch. 11).</ref> :-- For more on this, see, e.g., the chapter on [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|Fox, the Great Depression, the Great Recession, and our future]]. === The value of noncommercial news outlets === Some of the problems with the media and their contributions to increasing political polarization and violence are documented in the research summary on "[[Information is a public good: Designing experiments to improve government]]" and in the podcast series available on Wikiversity under "[[:Category:Media reform to improve democracy]]" with leading experts discussing their recommendations. One of the most compelling of the references discussed in that podcast series is Usher and Kim-Leffingwell (2022), who tallied all the federal prosecutions for political corruption in each of the 94 [[w:United States federal judicial district|US federal court district]]s between 2003 and 2019. During that period, the number of journalists in the US fell by a factor of roughly 3 -- between 60 and 70 percent. They found no statistically significant impact on federal prosecutions for political corruption of that decline in the number of journalists. However, each member of the [[w:Institute for Nonprofit News|Institute for Nonprofit News]] (INN) in a federal court district in one year was associated with on average 1.4 additional prosecutions for political corruption the following year. This suggests that the major media outlets that had so dramatically reduced their staffs had not substantively reduced the amount of investigative journalism they did. If we assume that the people prosecuted for political corruption also control substantive advertising budgets, then the major media outlets have conflicts of interest in honestly reporting on such. They may report on it if some other organization like a member of INN does the research and they are threatened with a loss of audience from not reporting on it. :'''''Major point''''': You and I benefit, the vast majority of humans on earth benefit, from news reports presumably published by members if INN that contributed to those on average 1.4 additional prosecutions for political corruption estimated by Usher and Kim-Leffingwell (2022). We benefit even if we never heard about the news reports that contributed to those prosecutions. We benefit even if we have never heard of the news outlets that presumably did the investigative journalism behind those additional prosecutions. Why? Because on average those news reports likely deterred other incidents of political corruption, which likely contributed to broadly shared economic growth and the development of new technology that ultimately benefit the vast majority of humanity. Other aspects of this are documented in the research on the impact of [[w:news desert|news desert]]s, which we summarize next. === Costs increase in news deserts=== There's a growing body of research describing what happens when local newspapers die. Perhaps most important, a 2018 research report by Gao et al. reported that the death of a local newspaper was followed by … increases in local tax revenue, averaging $85 per human per year.<ref name = Gao2018>Gao et al. (2018).</ref> That $85 was roughly 13 hundredths of a percent of the 2019 US GDP. That's mentioned in the 2025-07-17 interview with [[Democratic delusions: Fix the media to fix democracy|Natalie Fenton about her new book, ''Democratic Delusions, How the Media Hollows out democracy and What We Can Do About It'']]. One of the most spectacular example of the cost of a news desert is the [[w:City of Bell scandal|Scandal of Bell, California]]. Their local newspaper died around 1999. Roughly a decade later the city was nearly bankrupt in spite of having property tax rates among the highest in the nation. An investigation by the ''[[w:Los Angeles Times|Los Angeles Times]]'' documented that the city manager had a compensation package worth $1.5 million a year, well over double that of the President of the United States. Other senior city officials were similarly well-remunerated. Some of the city officials went to jail over that. Did the city manager decide after 1999, "Wow: The watchdog is dead. Let's have a party"? Malfeasance also increases in business as pollution and workplace accidents increase as does the cost of capital, because investors know their money is not as secure without a local newspaper. That leads to a reduction in investments in new products, services and processes -- slowing economic growth. See "[[Local newspapers limit malfeasance]]", esp. Kim et al. (2021). And executive compensation in increases in nonprofits, so less of what people donate goes to the charitable purpose for which they donated, according to Felix et al. (2024). Also, voter participation and split-ticket voting decline, per Benton (2019) and other references discussed in "[[Information is a public good: Designing experiments to improve government]]". And the ultra-right does better, as noted in [[News from Germany 1900-1945 and implications for today]] and the section on "[[Information is a public good: Designing experiments to improve government#Previous research|Previous research]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]".<ref>Flößer (2024).</ref> The 0.13 percent of GDP savings estimated by Gao et al. (2018) is roughly $120 per human per year. With over 300 million humans in the U.S, that is roughly $40 billion nationwide. {| class="wikitable" |+ Table 1. Costs increase in news deserts |- ! Entity !! What !!Source |- | local government || costs incr. 0.13% of GDP || Gao et al. (2018) |- | local businesses || pollution & workplace accidents incr., innovation & econ growth decr. || Kim et al. (2021) |- | nonprofits || exec. compensation incr. || Felix et al. (2024) |- | rowspan=2 | elections | voter participation & split-ticket voting decl. || Benton (2019) |- | Ultra-right does better || Flößer (2024) |} === Government subsidies for news === John (1995) documented how in the first half of the nineteenth century the US had more independent newspaper publishers per million population than at any other time or place in human history.<ref>This is discussed in the 2025-06-08 [[Media concentration per Columbia History Professor Richard John|interview with him]], available on Wikiversity under [[:Category:Media reform to improve democracy]], accessed 2026-04-30.</ref> This encouraged literacy and limited political corruption, both of which helped [[The Great American Paradox|the early United States stay together and grow]] while contemporary [[w:New Spain|New Spain]] / [[w:Mexico|Mexico]], fractured, shrank, and stagnated economically. As documented with Figure 1 in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]], that growth catapulted the young United States into its current position of dominance in the international political economy, a position it has been losing since at least 1990 -- or since the Reagan Revolution began in 1981, according to the analysis in the chapter below on [[/Fox, the Great Depression, the Great Recession, and our future/]]. Other countries now have stronger democracies due in part to government subsidies for media in the range of 0.05 and 0.25 percent of GDP with a firewall that limits political interference in the content, according to Neff and Pickard (2024). Table 1 in "[[Information is a public good: Designing experiments to improve government]] compares media subsidies in various places with "other points of reference". McChesney and Nichols (2010, pp. 310-311, note 88) suggested that the relatively high rate of economic growth of the economy in the early US was due in part to postal subsidies under the US [[w:Postal Service Act|Postal Service Act]] of 1792.<ref>See also the Wikiversity article on "[[The Great American Paradox]]", accessed 2026-04-30.</ref> They estimated those subsidies at 0.21 percent of GDP. To improve the current political economy of the US, they recommended subsidies of 0.15 percent of GDP distributed to local news nonprofits on the basis of local elections.<ref>McChesney and Nichols (2021, 2022).</ref> The Wikipedia article on "[[Information is a public good: Designing experiments to improve government]]" documents how some jurisdictions can devote that much money to local news nonprofits by matching what they spend on accounting, advertising, and public relations.<ref>See the section on "[[Information is a public good: Designing experiments to improve government#Sampling units / experimental polities|Sampling units / experimental polities]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]", accessed 2026-04-30.</ref> Pickard (2023) describes three basic strategies for confronting concentrated commercial media power: (1) break them up, (2) regulate them, and (3) create non-commercial, public alternatives. A fourth possibility might be [[w:externality|a graduated tax on income and wealth]] in proportion to the threat that major corporations pose to democracy. One class of noncommercial alternatives that Pickard mentions is local multimedia / Public Media Centers (PMCs) with management split between local journalists and boards, e.g., selected at random from registered voters. A key here is to have the boards selected in a way that cannot be influenced by people with power, whether business or political elites. Picard recommends considering '''six discrete layers''' when discussing PMCs, each of which, he says, must be radically democratised: # funding, # governance, # ascertainment (to determine a community’s ''critical information needs''), # infrastructure (including universal broadband service), # algorithmic (e.g., not allowing companies like Google and Facebook to suppress indexing information the might challenge their hegemony of those markets, [[w:Deep web|treating them like pedophilia and the Islamic State]]), # engagement, involving local communities in making their own news and in communicating their own stories; this is paramount to building trust and the grassroots-level support that this new local journalistic model requires. All this needs to be managed in ways that provide substantive support to news deserts and underserved communities that have long been subjected to various kinds of informational redlining. This might be done by including the proposed PMCs within local libraries staffed by professional journalists, who provide training in media literacy in local schools for children and supervise students producing school newspapers. PMCs could host regular, e.g., monthly events, where local residents could share their concerns with journalist, who would use that input to help prioritize different issues for news coverage. Journalist could also coach local residents in how to research issues and collaborate with journalists in producing news reports that may be better researched and more relevant to local concerns than could be produced without such collaboration. Management of such PMCs might be split between journalists on staff and boards of, e.g., six members selected at random from voter registration rolls serving staggered terms of one year with a new member rotated in every 2 months. Another alternative that could be done in parallel with local PMCs calls for 200 journalists in each US Congressional district funded at $10 billion annually in 2022 dollars, which is just a little under 4 hundredths of one percent of GDP; if such allocations are expressed as fractions of a percent of GDP, they would grow naturally with the economy. (The nominal GDP for the US was roughly $26.1 trillion in 2022.<ref>Johnston and Williamson (2026).</ref> For 2026 it is estimated at $32.4 trillion.<ref>[[w:United States|United States]], accessed 2026-04-30.</ref>) A similar model is the [[w:BBC|BBC]]’s Local Democracy Reporting Service (LDRS), in which the BBC funds journalists to cover the work of local councils and other local public bodies, funded at £8 million per year, which is a little under 2 hundredths of a percent of the [[w:United Kingdom|UK]]'s GDP of £7.27 trillion.<ref>[[w:United Kingdom|United Kingdom]], accessed 2026-04-30.</ref> Pickard (2023) ended by saying, "Today we face a crossroads: technocracy and oligarchy from above or radical democracy and structural reform from below. ... [T]his is not just a journalism crisis: it is a democracy crisis." ==Table of Contents== *[[/Introduction/]] including an exercise, asking all to discuss perceptions of the settlement of ''[[w:Dominion Voting Systems v. Fox News Network|Dominion Voting Systems v. Fox News Network]]'' in a friendly supportive manner with humans with whom they may vehemently disagree, because the alternative could be killing humans over misunderstandings. ===Part I. The media and political economy=== # [[/The impact of the media on political economy since the time of the Pharaohs/]] describes how religious leaders in hierarchical societies prior to [[w:James VI and I|King James of the King James bible]] convinced commoners to live in poverty while giving increasing shares of what they produced so religious and secular elites could live in opulence. During the reign of King James, pamphlets and newspapers began to compete with the church for helping commoners understand their roles in society. This produced the Industrial Revolution and modern democracies. Media consolidation since World War II slowed, then reversed this trend. # [[/Fox, the Great Depression, the Great Recession, and our future/]] describes the unprecedented performance of the US political economy during the presidency of Franklin Roosevelt (FDR), insisting that much of what FDR achieved can be replicated, giving a media system that supports honest discussion of the available evidence. # [[/Media consolidation, social media, and political polarization/]] (Combine from McChesney and Nichols discussing the [[w:Postal Service Act|US Postal Service Act]] of 1792 with [[Media concentration per Columbia History Professor Richard John]], the section on "[[v:Information is a public good: Designing experiments to improve government#Threats from social media|Threats from social media]]" in "[[Information is a public good: Designing experiments to improve government]], and the comments by [[v:Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen that, "the shortest path to a click is anger or hate."]]. ===Part II. The media and war=== # [[/Deterrence without threat/]]: The historical record is clear: Nations that have prepared for war often got war, not peace. This happens for at least two reasons: First, some leaders cannot resist the temptation to use force inappropriately, sometimes clandestinely provoking others to do things that are then denounced as "unprovoked"; sometimes the media environment pushes them to do such. Alternatively, potential adversaries may believe -- or claim -- that you are actually preparing a first strike, and they must move preemptively or lose their ability to retaliate adequately. We can avoid these possibilities with three supportive policies: [a] Legislation that ''prohibits'' projecting force beyond our own borders. [b] Civilian-based defense training in nonviolent noncooperation like what helped Denmark survive Nazi occupation with minimal damage. And [c] a media system that penalizes rather than encourages a bellicose foreign policy. # [[/Responding to a nuclear attack/]]: The ''worst'' response to a nuclear attack would be a nuclear response: The death toll from the 1945 [[w:Atomic bombings of Hiroshima and Nagasaki|Atomic bombings of Hiroshima and Nagasaki]] was estimated at between 150,000 and a quarter of a million. By contrast, simulations of nuclear wars of different magnitudes estimated that between 4 and 95 percent of humanity around the world would starve to death if they did not die of something else sooner. The range depends on whether the war was "limited", e.g., between India and Pakistan, and massive between the US and Russia. (Also add material from [[Nuclear weapons and effective defense]]). # [[/Threats from excessive government secrecy/]] (draft in [https://sanjosepeace.org/restrict-secrecy-more-than-data-collection/ "Restrict secrecy more than data collection"], adding material from [https://kkfi.org/program-episodes/does-us-government-secrecy-threaten-national-security/ Connelly (2023) ''The Declassification Engine: What History Reveals About America's Top Secrets''], [[Wikipedia:Moynihan Commission on Government Secrecy]] and [[1998 Embassy bombings and September 11]]. # [[/Shouting fire in a crowded theater/|Shouting ''fire'' in a crowded theater]]: Legal concerns about "[[w:Shouting fire in a crowded theater|Shouting ''fire'' in a crowded theater]]" date, at least in large part, from the [[w:Supreme Court of the United States|US Supreme Court]] decisions in ''[[w:Schenck v. United States|Schenck v. United States]]'' (1919) and ''[[w: Brandenburg v. Ohio| Brandenburg v. Ohio]]'' (1969). In ''Schenck'' the Court ruled that the government had a right to imprison Schenck and others, because their distribution of fliers encouraging draft resistance presented a [[w:clear and present danger|clear and present danger]] to the efficacy of ongoing military activities during [[w:World War I|World War I]], then in progress. The Court in ''Brandenburg'' held that the government cannot punish inflammatory speech ''unless that speech is "directed to inciting or producing imminent lawless action and is likely to incite or produce such action".'' Some could argue that many uses of military force by the US and Israel since 1948 have violated international law, encouraged by biases in the major US media "directed to inciting or producing imminent lawless action", though it may not be feasible to convince a court of that. Still, it might be useful to simulate such a case in a mock trial like the 1966 [[w:Russell Tribunal|Russell Tribunal]].<ref>Andersen (2006) provides such documentation for several such uses of force. Johnson (2026) ''How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza'' organizes evidence supporting such claims for the current [[w:Gaza war|Gaza war]], which began with [[w:October 7 attacks|Palestinian attacks 2023-10-07]]. See also Andersen (2026). Might, e.g., Palestinians -- or at least Palestinian Americans -- be able to sue the [[w:Anti-Defamation League|Anti-Defamation League]] (ADL), the [[w:AIPAC|American Israel Public Affairs Committee]] (AIPAC), and all the major media outlets in the US for inciting genocide in the current [[w:Gaza war|Gaza war]]? That history includes routine suppression of coverage by the major media especially in the US of routine denial of equal protection of Israeli laws to non-Jews in Israel and under Israeli occupation, including suppression of Israeli violence against nonviolent protestors peaceably assembling and petitioning for a redress of grievances combined with over reporting of Palestinian violence and unquestioning coverage of fraudulent claims of Palestinian violence by Israel and supporters. The suppressions included underreporting of Palestinian nonviolence such as the [[w:2018–2019 Gaza border protests|(2018-2019) Great March of Return]], and suppression of the grievances inspiring such nonviolence such as indefinite detention without charges of thousands of Palestinians, including children, routine destruction of Palestinian property by settlers, confiscation of Palestinian property at gunpoint, closing [[w:Gaza Strip|Gaza]] to international trade, and maintaining Gaza on starvation rations. These routine biases in reporting have been encouraged by charges that more honest reporting would be "[[w:Antisemitism|antisemetic]], according to the ADL and AIPAC. This denial of coverage thereby encouraged Israel to increase the rate of such violations until the [[w:October 7 attacks|2023-10-07 attacks on Israel from Gaza]] unleashed Israeli "retaliations" way out of proportion to the alleged provocation. Sucharov (2022) reported that 69% of American Jews opposed privileging Jews over non-Jews in Israel. Their support of Israel in the current Gaza war is consistent with the media biases documented by Johnson (2026) and others including Andersen (2006, 2026). Regarding whether Israel could achieve anything positive from this war, Samuelson (2025) is skeptical. He summarized quantitative analyses of 60 previous insurgencies. The results including the observation that it is exceedingly difficult to defeat an insurgency without responding to the grievances that support it without force ratios far beyond Israel's resources.</ref> ===Part III. Climate, immigrants, education, public health, and criminal justice=== # [[/Global warming/]] [Summarize research especially on conflicts of interest of major media in honestly reporting on this issue and the research on global warming itself and activities of groups concerned about this issue. Decompose into global population times CO2 equivalents per human.] # [[/Immigrants/]] [Summarize research documenting that [[w:Sanctuary city|sanctuary cities tend to have higher median incomes and no more crime than non-sanctuary jurisdictions]], and some studies report less crime. Moreover economists have documented that immigrants tend to be more entrepreneurial, overrepresented in patent applications, and generally increasing the rate of economic growth. See, e.g., Aghion et al. (2022) ''The power of creative destruction''; Aghion shared the 2025 Nobel Memorial Prize in Economics with two others.] # [[/Education/]] (draft in [[Invest in children]].) # [[/Public health/]] [Draft in [[UN public health data]] to be revised to be consistent with Bezruchka (2023, 2025).] # [[/Substance abuse and addictive behavior/]] (Research cited in "[[Wikipedia:War on drugs]]" insists that the US and the world would have fewer problems with substance abuse and addiction problems with 100 percent public funding for treatment programs and complete decriminalization of possession and use of retail quantities of addictive substances. We would also likely have fewer problems with immigrants, as that would make it harder for the US to intervene in the internal affairs of foreign countries funded off the books, as exposed in the [[w:Iran–Contra affair|Iran–Contra affair]]. See [[w:Alfred W. McCoy|Alfred W. McCoy]] (1972; 3rd ed. 2003) ''The politics of heroin''. Journalist [[w:Gary Webb|Gary Webb]] published similar claims that the US intervention in Nicaragua in the Iran-Contra Affair was funded in part by drug money. The story was officially retracted by the ''San José Mercury News'', and Webb allegedly killed himself with 2 bullets to the head. # [[/Criminal justice/]] (The section on "[[w:United States incarceration rate#Editorial policies of major media|Editorial policies of major media]]" in "[[Wikipedia:United States incarceration rate]]" cites research claiming that within the range range of experience in the US political economy since 1925, the incarceration rate is uncorrelated with crime: It's a function of the public's perception of crime, and that's a function of the media. That suggest that the US would be safer and more prosperous if incarceration policies were driving more by research than by editorial policies of the media. For example, there is also research that says that incarcerees who receive visits are less likely to recidivate, but that evidence is overlooked when convicts are incarcerated substantial distance from their family and friends and when the cost of phone services is substantially higher for incarcerees than among the general pubic. Also, it's known that better educated incarcerees are less likely to recidivate, but it's difficult and maybe impossible for many incarcerees to obtain education in prison.) # [[/Empower women and girls/]] [Cite research claiming that a primary restraint on population growth is empowering women and girls. Empowering women and girls is not just a matter of equity: It is also a means to reduce the threats of global warming, of increasing exposure to animal diseases and other problems that come with unrestrained population growth.] === Continuation === * [[/The evolving media literacy movement/]] to invite others to keep this book current with the evolving understanding of media literacy, how to encourage and promote it and the benefits of doing so. ==See also== * [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools]] ==Notes== {{reflist}} ==Bibliography== * <!--Daron Acemoğlu and Simon Johnson (2023) Power and Progress-->{{cite Q|Q125292212}} * <!--Robin Andersen (2006) A century of media, a century of war-->{{cite Q|Q138795568}} * <!--Robin Andersen (2026-06-02) The Complicit Lens: US Media Coverage of Israel’s Genocide in Gaza-->{{cite Q|Q138796307}} * <!--Perry Bacon Jr. (2022-10-17) "America Should Spend Billions to Revive Local News"-->{{cite Q|Q139594786}} * <!-- Joshua Benton (9 April 2019). "When local newspapers shrink, fewer people bother to run for mayor". Nieman Foundation for Journalism -->{{cite Q|Q63127216}} * <!--Stephen Bezruchka (2023) Inequality Kills Us All-->{{cite Q|Q136047815}} * <!--Stephen Bezruchka (2025) ''Born Sick in the USA''-->{{cite Q|Q138749292}} * <!--Renée DiResta (2024) Invisible Rulers: The People Who Turn Lies into Reality-->{{cite Q|Q135107164}} * <!--Robert Felix, Joshua A. Khavis, and Mikhail Pevzner (2024) "The effects of local newspaper closures on nonprofits’ executive compensation"-->{{cite Q|Q132730972}} * <!--Maxim Flößer (2024-03-06) "Keine Lokalzeitung -- mehr AfD", Kontext-->{{cite Q|Q125287792}} * <!--Pengjie Gao, Chang Lee, and Dermot Murphy (2018) "Financing Dies in Darkness? The Impact of Newspaper Closures on Public Finance"-->{{cite Q|Q55670016}} * <!--Spencer Graves (2024) "Wikipedia: The most democratic force on earth-->{{cite Q|Q137796922}} * <!--Spencer Graves and Bryan Bailey (2025) "We have to talk", blog at PeaceWorksKC.org-->{{cite Q|Q136126262}} * [[d:Q138038060|Dan Hind and Spencer Graves (2025) "Media Reform Coalition challenges anti-democratic media bias in the UK" on Wikiversity]]. * <!--Richard R. John (1995) Spreading the News: The American Postal System from Franklin to Morse-->{{cite Q|Q54641943}} * <!--Adam H. Johnson (2026-04-21) How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza-->{{cite Q|Q140073447}} * <!--Louis Johnston and Samuel H. Williamson, "What Was the U.S. GDP Then?" MeasuringWorth, 2026-->{{cite Q|Q56881105}} * <!-- Min Kim, Derrald Stice, Han Stice, and Roger M. White (2021) "Stop the presses! Or wait, we might need them: Firm responses to local newspaper closures and layoffs"-->{{cite Q|Q132459373}} * <!-- Robert W. McChesney; John Nichols (2010). The Death and Life of American Journalism (Bold Type Books) -->{{cite Q|Q104888067}}. * <!-- Robert W. McChesney; John Nichols (2021). "The Local Journalism Initiative: a proposal to protect and extend democracy". Columbia Journalism Review, 30 November 2021 -->{{cite Q|Q109978060}} * <!-- Robert W. McChesney; John Nichols (2022), To Protect and Extend Democracy, Recreate Local News Media (PDF), FreePress.net (updated 25 January 2022) -->{{cite Q|Q109978337|access-date=2024-06-23}} * <!--Alfred W. McCoy (2003-05-01) The politics of heroin : CIA complicity in the global drug trade : Afghanistan, Southeast Asia, Central America, Colombia-->{{cite Q|Q141317509}} * <!--Neff and Pickard (2024) "Funding Democracy: Public Media and Democratic Health in 33 Countries"-->{{cite Q|Q131468289}} * [[d:Q131398359|Victor Pickard (2020) ''Democracy without journalism? : confronting the misinformation society'' (Oxford U. Pr.)]]. * <!-- Victor Pickard (2023-05-12) "Another Media System is Possible: Ripping Open the Overton Window, from Platforms to Public Broadcasting"-->{{cite Q|Q131398460}} * <!--Doug Samuelson (2025) Assessing Israel’s Approach in Gaza-->{{cite Q|Q138843324}} * [[d:Q138037937|Dean Starkman and Spencer Graves (2025) "Dean Starkman and the watchdog that didn't bark anglais" on Wikiversity]]. * <!--Mira Sucharov (2022) Do American Jews Really Know What 'Zionist' Means?-->{{cite Q|Q125903777}} * [[d:Q134715465|Nikki Usher and Sanghoon Kim-Leffingwell (2022) "How Loud Does the Watchdog Bark? A Reconsideration of Local Journalism, News Non-profits, and Political Corruption", ''SSRN Electronic Journal'']]. * [[d:Q61013892|Horacio Verbitsky (1997) ''Un mundo sin periodistas'' (in Spanish: A world without journalists; Editorial Sudamericana)]]. [[Category:Communication]] [[Category:Political science]] [[Category:Law]] [[Category:Psychology]] [[Category:Sociology]] [[Category:Education]] [[Category:Economics]] [[Category:Media Literacy and You]] [[Category:Freedom and abundance]] <!-- https://en.wikiversity.org/wiki/Category_Review --> iy56wd0np6yvzjk952dywamhzj1d0yv 2835371 2835349 2026-10-01T17:23:42Z DavidMCEddy 218607 add discussion of "entrepreneurs of hate" 2835371 wikitext text/x-wiki [[File:Pharoah - James VI and I - Trump.png|thumb|Religious and media leaders from the time of the Pharaohs convinced common folk to give increasing shares of what they produced to elites.]] :''This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.'' == Invitation to edit this book == You, dear reader, are invited to contribute questions, ideas and citations to support or refute claims made in this book possibly adding chapters. Wikiversity like other Wikimedia Foundation Projects invites humans to [[w:Wikipedia:Be bold|“be bold but not reckless,”]] while writing from a [[Wikiversity:Disclosures|neutral point of view]], [[Wikiversity:Cite sources|citing credible sources]]. Others are invited to change or revert what you wrote. What stays tends to be written from a neutral point of view citing credible sources. If someone reverts your edit or you have a question, take it to the ''[[Wikiversity:FAQ|''''“Discuss”'''' page]]'' associated with the specific Wikiversity page most related to your concerns. Those who teach media literacy are encouraged to invite their students to debate and revise the contents of this book. Doing so would build on a tradition of [[:w:Wikipedia:Student assignments|instructors requiring students to edit wikipedia article(s).]] Editing [[:w:Wikipedia|Wikipedia]] and other [[:w:Wikimedia Foundation|Wikimedia Foundation]] projects like this book is itself an exercise in media literacy: :''Central tenets of media literacy might include writing from a neutral point of view citing credible sources and engaging others, some of whom may disagree, in civil, supportive conversations about what can and cannot be said based on a reasonable evaluation of the available evidence. Wikimedia rules invite contributors to do just that, encouraging them to “be bold but not reckless,” contributing revisions written from a neutral point of view, citing credible sources -- and raising other questions and concerns on the ''''“Discuss”'''' page associated with the specific Wikiversity page most related to your concerns, as mentioned above.''<ref>For more on this, see Graves (2024).</ref> == Text and self-help book and point of discuss == This book is intended both as a text and self-help book and as a point of discussion considering four levels of media literacy: :1. '''Think before you share''': Follow the money. Every media organization sells changes in audience behaviors to those who control much of their money. Major media everywhere promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to convince the public to give increasing shares of what they produce to elites to "protect them from designated evil others." To counter this, DiResta (2024, p. 335) recommends, "Think before you share." :2. '''Look for information to contradict preconceptions''' (Disconfirmation bias): [[w:Information is a public good: Designing experiments to improve government#Previous research|Virtually everyone]] (a) thinks they know more than they do ([[w:Overconfidence effect|overconfidence effect]]), and (b) prefers information and sources consistent with preconceptions ([[w:Confirmation bias|confirmation bias]]). The major media everywhere exploit this to please those who control most of the money for the media. Humans can counter this by searching for sources to help us understand our designated enemies. ''If we cannot explain circumstances under which we could see ourselves doing what we see our designated enemies doing, we haven't looked hard enough.'' :3. '''Talk''': Push ourselves to have friendly supportive conversations with others with whom we may vehemently disagree, seeking common ground, agreeing to disagree agreeably where we differ, and building collaboration on areas of common concern.<ref>Graves and Bailey (2025).</ref> :4. '''Teach''': Humans who develop skills in the first three levels can leverage that knowledge in helping others acquire those skills. If each one teaches two<ref>"[[:w:Each one teach one|Each one teach one]]" is an African-American proverb from the time of legalized slavery. However, if each one teaches only one, the growth in literacy will only be linear. Having "each one teaching two", on average, unleashes the power of doubling and [[:w:exponential growth|exponential growth]], which has the potential of educating the entirety of humanity in a reasonable period of time -- namely after 33 doublings starting from one.</ref> in a certain period of time, that time period becomes a [[:w:Doubling time|doubling time]]. Ten doublings is a thousand -- actually 1,024 to be precise.<ref>2 time 2 = 4 times 2 = 8 times 2 = 16 times 2 = 32 times 2 = 64 times 2 = 128 times 2 = 256 times 2 = 512 times 2 = 1024: That's 10 doublings, as anyone with a modest understanding of modern digital [[:w:computer|computer]]s will tell you.</ref> Twenty doublings become a million. Thirty doublings become a billion. Three more doublings become 8 billion, the [[:w:World population|world population]] as of approximately 2022-11-15.<ref>This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.</ref> Many organizations, including several United Nations agencies and the [[Yonty Friesem on media education|Media Education Lab]], already have active [[w:media literacy|media literacy]] programs that have already trained many.<ref>''[[Wikibooks:Antiracist Activism for Teachers and Students]]'' includes a chapter on [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools|Media Literacy In Schools]].</ref> This book is being written hoping to increase the effectiveness and accelerate the rate of growth in media literacy and thereby accelerate progress against many of the most pressing issues facing humanity today.<ref>[[w:Nolan Higdon|Nolan Higdon]] and Spencer Graves discussed marketing media literacy in a "[[:Category:Media reform to improve democracy|Media & Democracy]]" episode on, "[[Media literacy and why you should care]]".</ref> Much of this book is a [[w:Monograph|research monograph]] summarizing research that seems to have been underreported by the major media to avoid offending people who control most of the money for the media. These research results seem to be central to major political divisions. Each chapter ends in exercises to help the reader practice media literacy skills and have fun doing it. Remember: :''I am entitled to my [[Wiktionary:cockamamie|cockamamie]] ideas, and you are entitled to yours.'' Humor is important but must be offered in a way that does not offend others. If others are offended, they may be less interested in dialogue. The term "cockamamie" is used here, hoping that this style of [[w:Self-deprecation|self-deprecation]] might be more inviting for dialogue. ''Never say, "You're wrong." Instead, ask, "May I offer a contrary perspective?" Or "May I share with you another view that I've heard?"'' Much of the information in this book seems to have been largely overlooked and perhaps suppressed, apparently because it would either offend people who control substantial portions of the money for the media our would increase the cost of producing news; see the brief discussion of conflicts of interest by the major media in the next "Key claims" section. ==Key claims== * ''Primary drivers of every major conflict include differences between the media or difference in interpretation that the different parties find credible''. :-- This works, because everything we think we know is coded in systems of connections between neurons in our brains. These systems are more unique than fingerprints and evolve over time. The words we use do not mean the same to two different humans nor even to the same human at different points in time. In many cases these differences are inconsequential. ''Sometimes they are fatal.''<ref>Graves and Bailey (2026).</ref> :-- ''[[w:Social constructionism|Show me someone who knows the truth]], and I will show you someone who is dangerous'' -- especially during war or any other situation where humans may be moved to violence encouraged by their belief system.<ref>[[w:Collateral damage|Collateral damage]] that "they" commit proves to "us" that "they" are subhuman or at best criminally misled and must be resisted by any means necessary. By contrast, collateral damage that "we" commit is unfortunate but necessary.</ref> * ''The major media everywhere have [[w:Conflict of interest|conflicts of interest ]] in honestly reporting on [[v:Information is a public good per communications prof Pickard|anything that might offend anyone who controls large portions of the money for the media]].''<ref>Pickard and Graves (2025), accessed 2026-02-08; Pickard (2020).</ref> :--[[v:Media Reform Coalition challenges anti-democratic media bias in the UK|British journalist and media reform advocate Dan Hind]] said that the content produced by the [[w:BBC|BBC]] was frivolous, soap opera stuff, because leading media personalities know very little about issues of substance and believe "they might get in trouble if" they produced anything serious. Similar analyses seem to apply to the major media everywhere<ref>Hind and Graves (2025), accessed 2026-02-09.</ref> but may not apply to non-profit and local media, which seem more likely to produce [[w:Investigative journalism|investigative]] / [[v:Dean Starkman and the watchdog that didn't bark|accountability journalism]]:<ref>Usher and Kim-Leffingwell (2022); see also Starkman and Graves (2025), accessed 2026-02-09.</ref> [[w:Watchdog journalism|Watchdogs]] tend to protect the people who feed them. Argentine journalist [[w:Horacio Verbitsky|Horacio Verbitsky]] said, "Journalism is disseminating information that someone does not want known; the rest is [[w:propaganda|propaganda]]."<ref>p. 16 in Verbitsky (1997); English translation from [[Wikiquote:Horacio Verbitsky]], accessed 2026-02-09.</ref> * ''The major media everywhere create the stage upon which politicians read their lines.'' :-- Major media promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to make it easier for elites to pick everyone else's pockets. This is particularly effective with for-profit social media, which make money herding their audience into echo chambers, where erroneous preconceptions are reinforced, increasing political polarization and violence. [[Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen said]], "The shortest path to a click is anger or hate." A leading expert on for-profit social media is Renée DiResta,<ref>DiResta (2024).</ref> whose research documents how lies spread on social media threaten public health and prepped a small army of humans throughout the 2020 US presidential election cycle to believe that there were major deficiencies in the integrity of US election procedures. When Trump lost, he was able to recruit [[w:January 6 United States Capitol attack|a crowd to attack the capitol on January 6, 2021]]. Social media influencers made so much money spreading lies that it seemed profitable for them to file frivolous lawsuits ([[w:Strategic lawsuit against public participation|SLAPP]]), hoping that DiResta's legal bills would convince her to stop trying to expose their lies. After Republicans regained control of the US House in 2022, they subpoenaed her, claiming she had taken orders from the "[[w:Deep state|deep state]]" to tell Facebook to censor conservatives. [[Managing the good and the evils of social media|When interviewed for ''Media & Democracy'', she reported legal bills of $7 million]]. :-- The social psychology behind this phenomenon exploits especially [[w:confirmation bias|confirmation bias]]. It has contributed to [[Media Literacy and You/Media consolidation, social media, and political polarization|the dramatic increase in political polarization and violence worldwide]], especially since the end of the [[w:Fairness doctrine|Fairness doctrine]] in 1987. :-- Democracy may be best protected by local news nonprofits, managed jointly by journalists and boards selected at random from registered voters, according to Pickard (2023), discussed in the section below on "[[Media Literacy and You#Government subsidies for news|Government subsidies for news]]". :-- Their selection of acceptable topics for news and entertainment create and maintain the "[[w:Overton window|Overton window]]", which is the range of acceptable political discourse. For example, in early 1964, US President [[w:Lyndon B. Johnson|Lyndon Johnson]] understood that he could lose the 1964 presidential election that year if he were seen to be soft on communism. His response was to clandestinely provoke an attack on US naval vessels in the Gulf of Tonkin, which he could then denounce as "unprovoked". During a dark and stormy night 1964-08-04 the [[w:USS Maddox (DD-731)|USS ''Maddox'']] and [[w:USS Turner Joy|''Turner Joy'']] spent a couple of hours "defending themselves" against radar snow, then [[w:Gulf of Tonkin incident|reported that they had sunk two attacking North Vietnamese torpedo boats]]; subsequent investigations found no evidence of the reported attacks. That incident was used to justify the [[w:Gulf of Tonkin Resolution|Gulf of Tonkin Resolution]], with only two dissenting votes in the US Congress: Those two dissenters were defeated in their next reelection campaigns, illustrating the point that ::''the major media create the environment in which many politicians cannot get elected without betraying the nation.'' :-- Nick Hart,<ref name=Hart><!--Nick Hart-->{{cite Q|Q135663983}}</ref> President and CEO of the Data Foundation,<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> noted that President Trump in his first term signed the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] of 2019, which was bipartisan legislation ostensibly mandating evidence-informed public policy.<ref>Hart mentioned the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] when he was interviewed for [[Evidence-informed public policy|"Media & Democracy" 2025-07-31]].</ref> Tragically, the record since 2019 suggests that, ::''The US Congress is rarely allowed to consider solid research suppressed by the major media.'' * ''The development of technology is never neutral in its impact on inequality but is driven to benefit people with power.''<ref>Acemoglu and Johnson (2023)</ref>. :-- [[Media Literacy and You/The impact of the media on political economy since the time of the Pharaohs|Improvements in agricultural technology from pre-history to the time of King James of the King James bible were managed to benefit elites.]] Then pamphlets and newspapers began to appear, the head of state stopped granting as many monopolies, and commoners began getting permission to become entrepreneurs. That transformed economic stagnation into growth in GDP per capita adjusted for inflation, initiating the [[w:Industrial Revolution|Industrial Revolution]], as documented in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]]. It also led to increasing inequality until organized labor got enough political power to demand and get a bigger share of the fruits of their labors. :--[[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|In the US those benefits peaked during the Great Depression]], when the standard conservative mantra that blames the poor for their poverty did not sell newspapers. US President Franklin Roosevelt taxed the ultra-wealthy like they had never been taxed before or since, and dramatically reduced inequality, which continued to decline until increasing concentration of ownership of the media ushered in a new era of increasing inequality starting with the presidency of Ronald Reagan. :-- [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future#Role of the media|Acemoglu and Johnson insist that technology, including artificial intelligence, can be developed to benefit all. However, but it will not happen without action by the poor and middle class as follows]]: :# Alter the narrative, :# Build countervailing powers [like organized labor], and :# Develop technical, regulatory, and policy solutions to tackle specific aspects of technology’s social bias.<ref>Acemoglu and Johnson (2023, ch. 11).</ref> :-- For more on this, see, e.g., the chapter on [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|Fox, the Great Depression, the Great Recession, and our future]]. === The value of noncommercial news outlets === Some of the problems with the media and their contributions to increasing political polarization and violence are documented in the research summary on "[[Information is a public good: Designing experiments to improve government]]" and in the podcast series available on Wikiversity under "[[:Category:Media reform to improve democracy]]" with leading experts discussing their recommendations. One of the most compelling of the references discussed in that podcast series is Usher and Kim-Leffingwell (2022), who tallied all the federal prosecutions for political corruption in each of the 94 [[w:United States federal judicial district|US federal court district]]s between 2003 and 2019. During that period, the number of journalists in the US fell by a factor of roughly 3 -- between 60 and 70 percent. They found no statistically significant impact on federal prosecutions for political corruption of that decline in the number of journalists. However, each member of the [[w:Institute for Nonprofit News|Institute for Nonprofit News]] (INN) in a federal court district in one year was associated with on average 1.4 additional prosecutions for political corruption the following year. Since federal prosecutions for political corruption averaged roughly 10 per federal court district per year during that period. each member of INN in a federal court district one year was associated with a 14 percent increase in federal prosecutions the following year. This suggests that the major media outlets that had so dramatically reduced their staffs had not substantively reduced the amount of investigative journalism they did. If we assume that the people prosecuted for political corruption also control substantive advertising budgets, then the major media outlets have conflicts of interest in honestly reporting on such. They may report on it if some other organization like a member of INN does the research and they are threatened with a loss of audience from not reporting on it. :'''''Major point''''': You and I benefit, the vast majority of humans on earth benefit, from news reports presumably published by members of INN that contributed to those on average 1.4 additional prosecutions for political corruption estimated by Usher and Kim-Leffingwell (2022). We benefit even if we never heard about the news reports that contributed to those prosecutions. We benefit even if we have never heard of the news outlets that presumably did the investigative journalism behind those additional prosecutions. Why? Because on average those news reports likely deterred other incidents of political corruption, which likely contributed to broadly shared economic growth and the development of new technology that ultimately benefit the vast majority of humanity. Other aspects of this are documented in the research on the impact of [[w:news desert|news desert]]s, which we summarize next. === Costs increase in news deserts=== There's a growing body of research describing what happens when local newspapers die. Perhaps most important, a 2018 research report by Gao et al. reported that the death of a local newspaper was followed by … increases in local tax revenue, averaging $85 per human per year.<ref name = Gao2018>Gao et al. (2018).</ref> That $85 was roughly 13 hundredths of a percent of the 2019 US GDP. That's mentioned in the 2025-07-17 interview with [[Democratic delusions: Fix the media to fix democracy|Natalie Fenton about her new book, ''Democratic Delusions, How the Media Hollows out democracy and What We Can Do About It'']]. One of the most spectacular example of the cost of a news desert is the [[w:City of Bell scandal|Scandal of Bell, California]]. Their local newspaper died around 1999. Roughly a decade later the city was nearly bankrupt in spite of having property tax rates among the highest in the nation. An investigation by the ''[[w:Los Angeles Times|Los Angeles Times]]'' documented that the city manager had a compensation package worth $1.5 million a year, well over double that of the President of the United States. Other senior city officials were similarly well-remunerated. Some of the city officials went to jail over that. Did the city manager decide after 1999, "Wow: The watchdog is dead. Let's have a party"? Malfeasance also increases in business as pollution and workplace accidents increase as does the cost of capital, because investors know their money is not as secure without a local newspaper. That leads to a reduction in investments in new products, services and processes -- slowing economic growth. See "[[Local newspapers limit malfeasance]]", esp. Kim et al. (2021). And executive compensation in increases in nonprofits, so less of what people donate goes to the charitable purpose for which they donated, according to Felix et al. (2024). Also, voter participation and split-ticket voting decline, per Benton (2019) and other references discussed in "[[Information is a public good: Designing experiments to improve government]]". And the ultra-right does better, as noted in [[News from Germany 1900-1945 and implications for today]] and the section on "[[Information is a public good: Designing experiments to improve government#Previous research|Previous research]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]".<ref>Flößer (2024).</ref> The 0.13 percent of GDP savings estimated by Gao et al. (2018) is roughly $120 per human per year. With over 300 million humans in the U.S, that is roughly $40 billion nationwide. {| class="wikitable" |+ Table 1. Costs increase in news deserts |- ! Entity !! What !!Source |- | local government || costs incr. 0.13% of GDP || Gao et al. (2018) |- | local businesses || pollution & workplace accidents incr., innovation & econ growth decr. || Kim et al. (2021) |- | nonprofits || exec. compensation incr. || Felix et al. (2024) |- | rowspan=2 | elections | voter participation & split-ticket voting decl. || Benton (2019) |- | Ultra-right does better || Flößer (2024) |} === Government subsidies for news === John (1995) documented how in the first half of the nineteenth century the US had more independent newspaper publishers per million population than at any other time or place in human history.<ref>This is discussed in the 2025-06-08 [[Media concentration per Columbia History Professor Richard John|interview with him]], available on Wikiversity under [[:Category:Media reform to improve democracy]], accessed 2026-04-30.</ref> This encouraged literacy and limited political corruption, both of which helped [[The Great American Paradox|the early United States stay together and grow]] while contemporary [[w:New Spain|New Spain]] / [[w:Mexico|Mexico]], fractured, shrank, and stagnated economically. As documented with Figure 1 in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]], that growth catapulted the young United States into its current position of dominance in the international political economy, a position it has been losing since at least 1990 -- or since the Reagan Revolution began in 1981, according to the analysis in the chapter below on [[/Fox, the Great Depression, the Great Recession, and our future/]]. Other countries now have stronger democracies due in part to government subsidies for media in the range of 0.05 and 0.25 percent of GDP with a firewall that limits political interference in the content, according to Neff and Pickard (2024). Table 1 in "[[Information is a public good: Designing experiments to improve government]] compares media subsidies in various places with "other points of reference". McChesney and Nichols (2010, pp. 310-311, note 88) suggested that the relatively high rate of economic growth of the economy in the early US was due in part to postal subsidies under the US [[w:Postal Service Act|Postal Service Act]] of 1792.<ref>See also the Wikiversity article on "[[The Great American Paradox]]", accessed 2026-04-30.</ref> They estimated those subsidies at 0.21 percent of GDP. To improve the current political economy of the US, they recommended subsidies of 0.15 percent of GDP distributed to local news nonprofits on the basis of local elections.<ref>McChesney and Nichols (2021, 2022).</ref> The Wikipedia article on "[[Information is a public good: Designing experiments to improve government]]" documents how some jurisdictions can devote that much money to local news nonprofits by matching what they spend on accounting, advertising, and public relations.<ref>See the section on "[[Information is a public good: Designing experiments to improve government#Sampling units / experimental polities|Sampling units / experimental polities]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]", accessed 2026-04-30.</ref> Pickard (2023) describes three basic strategies for confronting concentrated commercial media power: (1) break them up, (2) regulate them, and (3) create non-commercial, public alternatives. A fourth possibility might be [[w:externality|a graduated tax on income and wealth]] in proportion to the threat that major corporations pose to democracy. One class of noncommercial alternatives that Pickard mentions is local multimedia / Public Media Centers (PMCs) with management split between local journalists and boards, e.g., selected at random from registered voters. A key here is to have the boards selected in a way that cannot be influenced by people with power, whether business or political elites. Picard recommends considering '''six discrete layers''' when discussing PMCs, each of which, he says, must be radically democratised: # funding, # governance, # ascertainment (to determine a community’s ''critical information needs''), # infrastructure (including universal broadband service), # algorithmic (e.g., not allowing companies like Google and Facebook to suppress indexing information the might challenge their hegemony of those markets, [[w:Deep web|treating them like pedophilia and the Islamic State]]), # engagement, involving local communities in making their own news and in communicating their own stories; this is paramount to building trust and the grassroots-level support that this new local journalistic model requires. All this needs to be managed in ways that provide substantive support to news deserts and underserved communities that have long been subjected to various kinds of informational redlining. This might be done by including the proposed PMCs within local libraries staffed by professional journalists, who provide training in media literacy in local schools for children and supervise students producing school newspapers. PMCs could host regular, e.g., monthly events, where local residents could share their concerns with journalist, who would use that input to help prioritize different issues for news coverage. Journalist could also coach local residents in how to research issues and collaborate with journalists in producing news reports that may be better researched and more relevant to local concerns than could be produced without such collaboration. Management of such PMCs might be split between journalists on staff and boards of, e.g., six members selected at random from voter registration rolls serving staggered terms of one year with a new member rotated in every 2 months. Another alternative that could be done in parallel with local PMCs calls for 200 journalists in each US Congressional district funded at $10 billion annually in 2022 dollars, which is just a little under 4 hundredths of one percent of GDP; if such allocations are expressed as fractions of a percent of GDP, they would grow naturally with the economy. (The nominal GDP for the US was roughly $26.1 trillion in 2022.<ref>Johnston and Williamson (2026).</ref> For 2026 it is estimated at $32.4 trillion.<ref>[[w:United States|United States]], accessed 2026-04-30.</ref>) A similar model is the [[w:BBC|BBC]]’s Local Democracy Reporting Service (LDRS), in which the BBC funds journalists to cover the work of local councils and other local public bodies, funded at £8 million per year, which is a little under 2 hundredths of a percent of the [[w:United Kingdom|UK]]'s GDP of £7.27 trillion.<ref>[[w:United Kingdom|United Kingdom]], accessed 2026-04-30.</ref> Pickard (2023) ended by saying, "Today we face a crossroads: technocracy and oligarchy from above or radical democracy and structural reform from below. ... [T]his is not just a journalism crisis: it is a democracy crisis." ==Table of Contents== *[[/Introduction/]] including an exercise, asking all to discuss perceptions of the settlement of ''[[w:Dominion Voting Systems v. Fox News Network|Dominion Voting Systems v. Fox News Network]]'' in a friendly supportive manner with humans with whom they may vehemently disagree, because the alternative could be killing humans over misunderstandings. ===Part I. The media and political economy=== # [[/The impact of the media on political economy since the time of the Pharaohs/]] describes how religious leaders in hierarchical societies prior to [[w:James VI and I|King James of the King James bible]] convinced commoners to live in poverty while giving increasing shares of what they produced so religious and secular elites could live in opulence. During the reign of King James, pamphlets and newspapers began to compete with the church for helping commoners understand their roles in society. This produced the Industrial Revolution and modern democracies. Media consolidation since World War II slowed, then reversed this trend. # [[/Fox, the Great Depression, the Great Recession, and our future/]] describes the unprecedented performance of the US political economy during the presidency of Franklin Roosevelt (FDR), insisting that much of what FDR achieved can be replicated, giving a media system that supports honest discussion of the available evidence. # [[/Media consolidation, social media, and political polarization/]] (Combine from McChesney and Nichols discussing the [[w:Postal Service Act|US Postal Service Act]] of 1792 with [[Media concentration per Columbia History Professor Richard John]], the section on "[[v:Information is a public good: Designing experiments to improve government#Threats from social media|Threats from social media]]" in "[[Information is a public good: Designing experiments to improve government]], and the comments by [[v:Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen that, "the shortest path to a click is anger or hate."]]. ===Part II. The media and war=== # [[/Deterrence without threat/]]: The historical record is clear: Nations that have prepared for war often got war, not peace. This happens for at least two reasons: First, some leaders cannot resist the temptation to use force inappropriately, sometimes clandestinely provoking others to do things that are then denounced as "unprovoked"; sometimes the media environment pushes them to do such. Alternatively, potential adversaries may believe -- or claim -- that you are actually preparing a first strike, and they must move preemptively or lose their ability to retaliate adequately. We can avoid these possibilities with three supportive policies: [a] Legislation that ''prohibits'' projecting force beyond our own borders. [b] Civilian-based defense training in nonviolent noncooperation like what helped Denmark survive Nazi occupation with minimal damage. And [c] a media system that penalizes rather than encourages a bellicose foreign policy. # [[/Responding to a nuclear attack/]]: The ''worst'' response to a nuclear attack would be a nuclear response: The death toll from the 1945 [[w:Atomic bombings of Hiroshima and Nagasaki|Atomic bombings of Hiroshima and Nagasaki]] was estimated at between 150,000 and a quarter of a million. By contrast, simulations of nuclear wars of different magnitudes estimated that between 4 and 95 percent of humanity around the world would starve to death if they did not die of something else sooner. The range depends on whether the war was "limited", e.g., between India and Pakistan, and massive between the US and Russia. (Also add material from [[Nuclear weapons and effective defense]]). # [[/Threats from excessive government secrecy/]] (draft in [https://sanjosepeace.org/restrict-secrecy-more-than-data-collection/ "Restrict secrecy more than data collection"], adding material from [https://kkfi.org/program-episodes/does-us-government-secrecy-threaten-national-security/ Connelly (2023) ''The Declassification Engine: What History Reveals About America's Top Secrets''], [[Wikipedia:Moynihan Commission on Government Secrecy]] and [[1998 Embassy bombings and September 11]]. # [[/Shouting fire in a crowded theater/|Shouting ''fire'' in a crowded theater]]: Legal concerns about "[[w:Shouting fire in a crowded theater|Shouting ''fire'' in a crowded theater]]" date, at least in large part, from the [[w:Supreme Court of the United States|US Supreme Court]] decisions in ''[[w:Schenck v. United States|Schenck v. United States]]'' (1919) and ''[[w: Brandenburg v. Ohio| Brandenburg v. Ohio]]'' (1969). In ''Schenck'' the Court ruled that the government had a right to imprison Schenck and others, because their distribution of fliers encouraging draft resistance presented a [[w:clear and present danger|clear and present danger]] to the efficacy of ongoing military activities during [[w:World War I|World War I]], then in progress. The Court in ''Brandenburg'' held that the government cannot punish inflammatory speech ''unless that speech is "directed to inciting or producing imminent lawless action and is likely to incite or produce such action".'' Some could argue that many uses of military force by the US and Israel since 1948 have violated international law, encouraged by biases in the major US media "directed to inciting or producing imminent lawless action", though it may not be feasible to convince a court of that. Still, it might be useful to simulate such a case in a mock trial like the 1966 [[w:Russell Tribunal|Russell Tribunal]].<ref>Andersen (2006) provides such documentation for several such uses of force. Andersen (2026) and Johnson (2026) organize evidence supporting such claims for the current [[w:Gaza war|Gaza war]], which began with [[w:October 7 attacks|Palestinian attacks 2023-10-07]]. Might, e.g., Palestinians -- or at least Palestinian Americans -- be able to sue the [[w:Anti-Defamation League|Anti-Defamation League]] (ADL), the [[w:AIPAC|American Israel Public Affairs Committee]] (AIPAC), and all the major media outlets in the US for inciting genocide in the current [[w:Gaza war|Gaza war]]? That history includes routine suppression of coverage by the major media especially in the US of routine denial of equal protection of Israeli laws to non-Jews in Israel and under Israeli occupation, including suppression of Israeli violence against nonviolent protestors peaceably assembling and petitioning for a redress of grievances combined with over reporting of Palestinian violence and unquestioning coverage of fraudulent claims of Palestinian violence by Israel and supporters. The suppressions included underreporting of Palestinian nonviolence such as the [[w:2018–2019 Gaza border protests|(2018-2019) Great March of Return]], and suppression of the grievances inspiring such nonviolence such as indefinite detention without charges of thousands of Palestinians, including children, routine destruction of Palestinian property by settlers, confiscation of Palestinian property at gunpoint, closing [[w:Gaza Strip|Gaza]] to international trade, and maintaining Gaza on starvation rations. These routine biases in reporting have been encouraged by charges that more honest reporting would be "[[w:Antisemitism|antisemetic]], according to the ADL and AIPAC. This denial of coverage thereby encouraged Israel to increase the rate of such violations until the [[w:October 7 attacks|2023-10-07 attacks on Israel from Gaza]] unleashed Israeli "retaliations" way out of proportion to the alleged provocation. Sucharov (2022) reported that 69% of American Jews opposed privileging Jews over non-Jews in Israel. Their support of Israel in the current Gaza war is consistent with the media biases documented by Johnson (2026) and others including Andersen (2006, 2026). Regarding whether Israel could achieve anything positive from this war, Samuelson (2025) is skeptical. He summarized quantitative analyses of 60 previous insurgencies. The results including the observation that it is exceedingly difficult to defeat an insurgency without responding to the grievances that support it without force ratios far beyond Israel's resources.</ref> ===Part III. Climate, immigrants, education, public health, and criminal justice=== # [[/Global warming/]] [Summarize research especially on conflicts of interest of major media in honestly reporting on this issue and the research on global warming itself and activities of groups concerned about this issue. Decompose into global population times CO2 equivalents per human.] # [[/Immigrants/]] [Summarize research documenting that [[w:Sanctuary city|sanctuary cities tend to have higher median incomes and no more crime than non-sanctuary jurisdictions]], and some studies report less crime. Moreover economists have documented that immigrants tend to be more entrepreneurial, overrepresented in patent applications, and generally increasing the rate of economic growth. See, e.g., Aghion et al. (2022) ''The power of creative destruction''; Aghion shared the 2025 Nobel Memorial Prize in Economics with two others.] # [[/Education/]] (draft in [[Invest in children]].) # [[/Public health/]] [Draft in [[UN public health data]] to be revised to be consistent with Bezruchka (2023, 2025).] # [[/Substance abuse and addictive behavior/]] (Research cited in "[[Wikipedia:War on drugs]]" insists that the US and the world would have fewer problems with substance abuse and addiction problems with 100 percent public funding for treatment programs and complete decriminalization of possession and use of retail quantities of addictive substances. We would also likely have fewer problems with immigrants, as that would make it harder for the US to intervene in the internal affairs of foreign countries funded off the books, as exposed in the [[w:Iran–Contra affair|Iran–Contra affair]]. See [[w:Alfred W. McCoy|Alfred W. McCoy]] (1972; 3rd ed. 2003) ''The politics of heroin''. Journalist [[w:Gary Webb|Gary Webb]] published similar claims that the US intervention in Nicaragua in the Iran-Contra Affair was funded in part by drug money. The story was officially retracted by the ''San José Mercury News'', and Webb allegedly killed himself with 2 bullets to the head. # [[/Criminal justice/]] (The section on "[[w:United States incarceration rate#Editorial policies of major media|Editorial policies of major media]]" in "[[Wikipedia:United States incarceration rate]]" cites research claiming that within the range range of experience in the US political economy since 1925, the incarceration rate is uncorrelated with crime: It's a function of the public's perception of crime, and that's a function of the media. That suggest that the US would be safer and more prosperous if incarceration policies were driving more by research than by editorial policies of the media. For example, there is also research that says that incarcerees who receive visits are less likely to recidivate, but that evidence is overlooked when convicts are incarcerated substantial distance from their family and friends and when the cost of phone services is substantially higher for incarcerees than among the general pubic. Also, it's known that better educated incarcerees are less likely to recidivate, but it's difficult and maybe impossible for many incarcerees to obtain education in prison.) # [[/Empower women and girls/]] [Cite research claiming that a primary restraint on population growth is empowering women and girls. Empowering women and girls is not just a matter of equity: It is also a means to reduce the threats of global warming, of increasing exposure to animal diseases and other problems that come with unrestrained population growth.] === Continuation === * [[/The evolving media literacy movement/]] to invite others to keep this book current with the evolving understanding of media literacy, how to encourage and promote it and the benefits of doing so. ==See also== * [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools]] ==Notes== {{reflist}} ==Bibliography== * <!--Daron Acemoğlu and Simon Johnson (2023) Power and Progress-->{{cite Q|Q125292212}} * <!--Robin Andersen (2006) A century of media, a century of war-->{{cite Q|Q138795568}} * <!--Robin Andersen (2026-06-02) The Complicit Lens: US Media Coverage of Israel’s Genocide in Gaza-->{{cite Q|Q138796307}} * <!--Perry Bacon Jr. (2022-10-17) "America Should Spend Billions to Revive Local News"-->{{cite Q|Q139594786}} * <!-- Joshua Benton (9 April 2019). "When local newspapers shrink, fewer people bother to run for mayor". Nieman Foundation for Journalism -->{{cite Q|Q63127216}} * <!--Stephen Bezruchka (2023) Inequality Kills Us All-->{{cite Q|Q136047815}} * <!--Stephen Bezruchka (2025) ''Born Sick in the USA''-->{{cite Q|Q138749292}} * <!--Renée DiResta (2024) Invisible Rulers: The People Who Turn Lies into Reality-->{{cite Q|Q135530439}} * <!--Robert Felix, Joshua A. Khavis, and Mikhail Pevzner (2024) "The effects of local newspaper closures on nonprofits’ executive compensation"-->{{cite Q|Q132730972}} * <!--Maxim Flößer (2024-03-06) "Keine Lokalzeitung -- mehr AfD", Kontext-->{{cite Q|Q125287792}} * <!--Pengjie Gao, Chang Lee, and Dermot Murphy (2018) "Financing Dies in Darkness? The Impact of Newspaper Closures on Public Finance"-->{{cite Q|Q55670016}} * <!--Spencer Graves (2024) "Wikipedia: The most democratic force on earth-->{{cite Q|Q137796922}} * <!--Spencer Graves and Bryan Bailey (2025) "We have to talk", blog at PeaceWorksKC.org-->{{cite Q|Q136126262}} * [[d:Q138038060|Dan Hind and Spencer Graves (2025) "Media Reform Coalition challenges anti-democratic media bias in the UK" on Wikiversity]]. * <!--Richard R. John (1995) Spreading the News: The American Postal System from Franklin to Morse-->{{cite Q|Q54641943}} * <!--Adam H. Johnson (2026-04-21) How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza-->{{cite Q|Q140073447}} * <!--Louis Johnston and Samuel H. Williamson, "What Was the U.S. GDP Then?" MeasuringWorth, 2026-->{{cite Q|Q56881105}} * <!-- Min Kim, Derrald Stice, Han Stice, and Roger M. White (2021) "Stop the presses! Or wait, we might need them: Firm responses to local newspaper closures and layoffs"-->{{cite Q|Q132459373}} * <!-- Robert W. McChesney; John Nichols (2010). The Death and Life of American Journalism (Bold Type Books) -->{{cite Q|Q104888067}}. * <!-- Robert W. McChesney; John Nichols (2021). "The Local Journalism Initiative: a proposal to protect and extend democracy". Columbia Journalism Review, 30 November 2021 -->{{cite Q|Q109978060}} * <!-- Robert W. McChesney; John Nichols (2022), To Protect and Extend Democracy, Recreate Local News Media (PDF), FreePress.net (updated 25 January 2022) -->{{cite Q|Q109978337|access-date=2024-06-23}} * <!--Alfred W. McCoy (2003-05-01) The politics of heroin : CIA complicity in the global drug trade : Afghanistan, Southeast Asia, Central America, Colombia-->{{cite Q|Q141317509}} * <!--Joel Mokyr (2017) A Culture of Growth: The Origins of the Modern Economy (Graz Schumpeter Lectures; Princeton University Press)-->{{cite Q|Q136118590}} * <!--Neff and Pickard (2024) "Funding Democracy: Public Media and Democratic Health in 33 Countries"-->{{cite Q|Q131468289}} * [[d:Q131398359|Victor Pickard (2020) ''Democracy without journalism? : confronting the misinformation society'' (Oxford U. Pr.)]]. * <!-- Victor Pickard (2023-05-12) "Another Media System is Possible: Ripping Open the Overton Window, from Platforms to Public Broadcasting"-->{{cite Q|Q131398460}} * <!--Doug Samuelson (2025) Assessing Israel’s Approach in Gaza-->{{cite Q|Q138843324}} * [[d:Q138037937|Dean Starkman and Spencer Graves (2025) "Dean Starkman and the watchdog that didn't bark anglais" on Wikiversity]]. * <!--Mira Sucharov (2022) Do American Jews Really Know What 'Zionist' Means?-->{{cite Q|Q125903777}} * [[d:Q134715465|Nikki Usher and Sanghoon Kim-Leffingwell (2022) "How Loud Does the Watchdog Bark? A Reconsideration of Local Journalism, News Non-profits, and Political Corruption", ''SSRN Electronic Journal'']]. * [[d:Q61013892|Horacio Verbitsky (1997) ''Un mundo sin periodistas'' (in Spanish: A world without journalists; Editorial Sudamericana)]]. [[Category:Communication]] [[Category:Political science]] [[Category:Law]] [[Category:Psychology]] [[Category:Sociology]] [[Category:Education]] [[Category:Economics]] [[Category:Media Literacy and You]] [[Category:Freedom and abundance]] <!-- https://en.wikiversity.org/wiki/Category_Review --> 6l50exo1v8pgegf3awu3p535iry15p4 2835372 2835371 2026-10-01T17:25:27Z DavidMCEddy 218607 wdsmth 2835372 wikitext text/x-wiki [[File:Pharoah - James VI and I - Trump.png|thumb|Religious and media leaders from the time of the Pharaohs convinced common folk to give increasing shares of what they produced to elites.]] :''This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.'' == Invitation to edit this book == You, dear reader, are invited to contribute questions, ideas and citations to support or refute claims made in this book possibly adding chapters. Wikiversity like other Wikimedia Foundation Projects invites humans to [[w:Wikipedia:Be bold|“be bold but not reckless,”]] while writing from a [[Wikiversity:Disclosures|neutral point of view]], [[Wikiversity:Cite sources|citing credible sources]]. Others are invited to change or revert what you wrote. What stays tends to be written from a neutral point of view citing credible sources. If someone reverts your edit or you have a question, take it to the ''[[Wikiversity:FAQ|''''“Discuss”'''' page]]'' associated with the specific Wikiversity page most related to your concerns. Those who teach media literacy are encouraged to invite their students to debate and revise the contents of this book. Doing so would build on a tradition of [[:w:Wikipedia:Student assignments|instructors requiring students to edit wikipedia article(s).]] Editing [[:w:Wikipedia|Wikipedia]] and other [[:w:Wikimedia Foundation|Wikimedia Foundation]] projects like this book is itself an exercise in media literacy: :''Central tenets of media literacy might include writing from a neutral point of view citing credible sources and engaging others, some of whom may disagree, in civil, supportive conversations about what can and cannot be said based on a reasonable evaluation of the available evidence. Wikimedia rules invite contributors to do just that, encouraging them to “be bold but not reckless,” contributing revisions written from a neutral point of view, citing credible sources -- and raising other questions and concerns on the ''''“Discuss”'''' page associated with the specific Wikiversity page most related to your concerns, as mentioned above.''<ref>For more on this, see Graves (2024).</ref> == Text and self-help book and point of discuss == This book is intended both as a text and self-help book and as a point of discussion considering four levels of media literacy: :1. '''Think before you share''': Follow the money. Every media organization sells changes in audience behaviors to those who control much of their money. Major media everywhere promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to convince the public to give increasing shares of what they produce to elites to "protect them from designated evil others." To counter this, DiResta (2024, p. 335) recommends, "Think before you share." :2. '''Look for information to contradict preconceptions''' (Disconfirmation bias): [[w:Information is a public good: Designing experiments to improve government#Previous research|Virtually everyone]] (a) thinks they know more than they do ([[w:Overconfidence effect|overconfidence effect]]), and (b) prefers information and sources consistent with preconceptions ([[w:Confirmation bias|confirmation bias]]). The major media everywhere exploit this to please those who control most of the money for the media. Humans can counter this by searching for sources to help us understand our designated enemies. ''If we cannot explain circumstances under which we could see ourselves doing what we see our designated enemies doing, we have not looked hard enough.'' :3. '''Talk''': Push ourselves to have friendly supportive conversations with others with whom we may vehemently disagree, seeking common ground, agreeing to disagree agreeably where we differ, and building collaboration on areas of common concern.<ref>Graves and Bailey (2025).</ref> :4. '''Teach''': Humans who develop skills in the first three levels can leverage that knowledge in helping others acquire those skills. If each one teaches two<ref>"[[:w:Each one teach one|Each one teach one]]" is an African-American proverb from the time of legalized slavery. However, if each one teaches only one, the growth in literacy will only be linear. Having "each one teaching two", on average, unleashes the power of doubling and [[:w:exponential growth|exponential growth]], which has the potential of educating the entirety of humanity in a reasonable period of time -- namely after 33 doublings starting from one.</ref> in a certain period of time, that time period becomes a [[:w:Doubling time|doubling time]]. Ten doublings is a thousand -- actually 1,024 to be precise.<ref>2 time 2 = 4 times 2 = 8 times 2 = 16 times 2 = 32 times 2 = 64 times 2 = 128 times 2 = 256 times 2 = 512 times 2 = 1024: That's 10 doublings, as anyone with a modest understanding of modern digital [[:w:computer|computer]]s will tell you.</ref> Twenty doublings become a million. Thirty doublings become a billion. Three more doublings become 8 billion, the [[:w:World population|world population]] as of approximately 2022-11-15.<ref>This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.</ref> Many organizations, including several United Nations agencies and the [[Yonty Friesem on media education|Media Education Lab]], already have active [[w:media literacy|media literacy]] programs that have already trained many.<ref>''[[Wikibooks:Antiracist Activism for Teachers and Students]]'' includes a chapter on [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools|Media Literacy In Schools]].</ref> This book is being written hoping to increase the effectiveness and accelerate the rate of growth in media literacy and thereby accelerate progress against many of the most pressing issues facing humanity today.<ref>[[w:Nolan Higdon|Nolan Higdon]] and Spencer Graves discussed marketing media literacy in a "[[:Category:Media reform to improve democracy|Media & Democracy]]" episode on, "[[Media literacy and why you should care]]".</ref> Much of this book is a [[w:Monograph|research monograph]] summarizing research that seems to have been underreported by the major media to avoid offending people who control most of the money for the media. These research results seem to be central to major political divisions. Each chapter ends in exercises to help the reader practice media literacy skills and have fun doing it. Remember: :''I am entitled to my [[Wiktionary:cockamamie|cockamamie]] ideas, and you are entitled to yours.'' Humor is important but must be offered in a way that does not offend others. If others are offended, they may be less interested in dialogue. The term "cockamamie" is used here, hoping that this style of [[w:Self-deprecation|self-deprecation]] might be more inviting for dialogue. ''Never say, "You're wrong." Instead, ask, "May I offer a contrary perspective?" Or "May I share with you another view that I've heard?"'' Much of the information in this book seems to have been largely overlooked and perhaps suppressed, apparently because it would either offend people who control substantial portions of the money for the media our would increase the cost of producing news; see the brief discussion of conflicts of interest by the major media in the next "Key claims" section. ==Key claims== * ''Primary drivers of every major conflict include differences between the media or difference in interpretation that the different parties find credible''. :-- This works, because everything we think we know is coded in systems of connections between neurons in our brains. These systems are more unique than fingerprints and evolve over time. The words we use do not mean the same to two different humans nor even to the same human at different points in time. In many cases these differences are inconsequential. ''Sometimes they are fatal.''<ref>Graves and Bailey (2026).</ref> :-- ''[[w:Social constructionism|Show me someone who knows the truth]], and I will show you someone who is dangerous'' -- especially during war or any other situation where humans may be moved to violence encouraged by their belief system.<ref>[[w:Collateral damage|Collateral damage]] that "they" commit proves to "us" that "they" are subhuman or at best criminally misled and must be resisted by any means necessary. By contrast, collateral damage that "we" commit is unfortunate but necessary.</ref> * ''The major media everywhere have [[w:Conflict of interest|conflicts of interest ]] in honestly reporting on [[v:Information is a public good per communications prof Pickard|anything that might offend anyone who controls large portions of the money for the media]].''<ref>Pickard and Graves (2025), accessed 2026-02-08; Pickard (2020).</ref> :--[[v:Media Reform Coalition challenges anti-democratic media bias in the UK|British journalist and media reform advocate Dan Hind]] said that the content produced by the [[w:BBC|BBC]] was frivolous, soap opera stuff, because leading media personalities know very little about issues of substance and believe "they might get in trouble if" they produced anything serious. Similar analyses seem to apply to the major media everywhere<ref>Hind and Graves (2025), accessed 2026-02-09.</ref> but may not apply to non-profit and local media, which seem more likely to produce [[w:Investigative journalism|investigative]] / [[v:Dean Starkman and the watchdog that didn't bark|accountability journalism]]:<ref>Usher and Kim-Leffingwell (2022); see also Starkman and Graves (2025), accessed 2026-02-09.</ref> [[w:Watchdog journalism|Watchdogs]] tend to protect the people who feed them. Argentine journalist [[w:Horacio Verbitsky|Horacio Verbitsky]] said, "Journalism is disseminating information that someone does not want known; the rest is [[w:propaganda|propaganda]]."<ref>p. 16 in Verbitsky (1997); English translation from [[Wikiquote:Horacio Verbitsky]], accessed 2026-02-09.</ref> * ''The major media everywhere create the stage upon which politicians read their lines.'' :-- Major media promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to make it easier for elites to pick everyone else's pockets. This is particularly effective with for-profit social media, which make money herding their audience into echo chambers, where erroneous preconceptions are reinforced, increasing political polarization and violence. [[Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen said]], "The shortest path to a click is anger or hate." A leading expert on for-profit social media is Renée DiResta,<ref>DiResta (2024).</ref> whose research documents how lies spread on social media threaten public health and prepped a small army of humans throughout the 2020 US presidential election cycle to believe that there were major deficiencies in the integrity of US election procedures. When Trump lost, he was able to recruit [[w:January 6 United States Capitol attack|a crowd to attack the capitol on January 6, 2021]]. Social media influencers made so much money spreading lies that it seemed profitable for them to file frivolous lawsuits ([[w:Strategic lawsuit against public participation|SLAPP]]), hoping that DiResta's legal bills would convince her to stop trying to expose their lies. After Republicans regained control of the US House in 2022, they subpoenaed her, claiming she had taken orders from the "[[w:Deep state|deep state]]" to tell Facebook to censor conservatives. [[Managing the good and the evils of social media|When interviewed for ''Media & Democracy'', she reported legal bills of $7 million]]. :-- The social psychology behind this phenomenon exploits especially [[w:confirmation bias|confirmation bias]]. It has contributed to [[Media Literacy and You/Media consolidation, social media, and political polarization|the dramatic increase in political polarization and violence worldwide]], especially since the end of the [[w:Fairness doctrine|Fairness doctrine]] in 1987. :-- Democracy may be best protected by local news nonprofits, managed jointly by journalists and boards selected at random from registered voters, according to Pickard (2023), discussed in the section below on "[[Media Literacy and You#Government subsidies for news|Government subsidies for news]]". :-- Their selection of acceptable topics for news and entertainment create and maintain the "[[w:Overton window|Overton window]]", which is the range of acceptable political discourse. For example, in early 1964, US President [[w:Lyndon B. Johnson|Lyndon Johnson]] understood that he could lose the 1964 presidential election that year if he were seen to be soft on communism. His response was to clandestinely provoke an attack on US naval vessels in the Gulf of Tonkin, which he could then denounce as "unprovoked". During a dark and stormy night 1964-08-04 the [[w:USS Maddox (DD-731)|USS ''Maddox'']] and [[w:USS Turner Joy|''Turner Joy'']] spent a couple of hours "defending themselves" against radar snow, then [[w:Gulf of Tonkin incident|reported that they had sunk two attacking North Vietnamese torpedo boats]]; subsequent investigations found no evidence of the reported attacks. That incident was used to justify the [[w:Gulf of Tonkin Resolution|Gulf of Tonkin Resolution]], with only two dissenting votes in the US Congress: Those two dissenters were defeated in their next reelection campaigns, illustrating the point that ::''the major media create the environment in which many politicians cannot get elected without betraying the nation.'' :-- Nick Hart,<ref name=Hart><!--Nick Hart-->{{cite Q|Q135663983}}</ref> President and CEO of the Data Foundation,<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> noted that President Trump in his first term signed the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] of 2019, which was bipartisan legislation ostensibly mandating evidence-informed public policy.<ref>Hart mentioned the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] when he was interviewed for [[Evidence-informed public policy|"Media & Democracy" 2025-07-31]].</ref> Tragically, the record since 2019 suggests that, ::''The US Congress is rarely allowed to consider solid research suppressed by the major media.'' * ''The development of technology is never neutral in its impact on inequality but is driven to benefit people with power.''<ref>Acemoglu and Johnson (2023)</ref>. :-- [[Media Literacy and You/The impact of the media on political economy since the time of the Pharaohs|Improvements in agricultural technology from pre-history to the time of King James of the King James bible were managed to benefit elites.]] Then pamphlets and newspapers began to appear, the head of state stopped granting as many monopolies, and commoners began getting permission to become entrepreneurs. That transformed economic stagnation into growth in GDP per capita adjusted for inflation, initiating the [[w:Industrial Revolution|Industrial Revolution]], as documented in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]]. It also led to increasing inequality until organized labor got enough political power to demand and get a bigger share of the fruits of their labors. :--[[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|In the US those benefits peaked during the Great Depression]], when the standard conservative mantra that blames the poor for their poverty did not sell newspapers. US President Franklin Roosevelt taxed the ultra-wealthy like they had never been taxed before or since, and dramatically reduced inequality, which continued to decline until increasing concentration of ownership of the media ushered in a new era of increasing inequality starting with the presidency of Ronald Reagan. :-- [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future#Role of the media|Acemoglu and Johnson insist that technology, including artificial intelligence, can be developed to benefit all. However, but it will not happen without action by the poor and middle class as follows]]: :# Alter the narrative, :# Build countervailing powers [like organized labor], and :# Develop technical, regulatory, and policy solutions to tackle specific aspects of technology’s social bias.<ref>Acemoglu and Johnson (2023, ch. 11).</ref> :-- For more on this, see, e.g., the chapter on [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|Fox, the Great Depression, the Great Recession, and our future]]. === The value of noncommercial news outlets === Some of the problems with the media and their contributions to increasing political polarization and violence are documented in the research summary on "[[Information is a public good: Designing experiments to improve government]]" and in the podcast series available on Wikiversity under "[[:Category:Media reform to improve democracy]]" with leading experts discussing their recommendations. One of the most compelling of the references discussed in that podcast series is Usher and Kim-Leffingwell (2022), who tallied all the federal prosecutions for political corruption in each of the 94 [[w:United States federal judicial district|US federal court district]]s between 2003 and 2019. During that period, the number of journalists in the US fell by a factor of roughly 3 -- between 60 and 70 percent. They found no statistically significant impact on federal prosecutions for political corruption of that decline in the number of journalists. However, each member of the [[w:Institute for Nonprofit News|Institute for Nonprofit News]] (INN) in a federal court district in one year was associated with on average 1.4 additional prosecutions for political corruption the following year. Since federal prosecutions for political corruption averaged roughly 10 per federal court district per year during that period. each member of INN in a federal court district one year was associated with a 14 percent increase in federal prosecutions the following year. This suggests that the major media outlets that had so dramatically reduced their staffs had not substantively reduced the amount of investigative journalism they did. If we assume that the people prosecuted for political corruption also control substantive advertising budgets, then the major media outlets have conflicts of interest in honestly reporting on such. They may report on it if some other organization like a member of INN does the research and they are threatened with a loss of audience from not reporting on it. :'''''Major point''''': You and I benefit, the vast majority of humans on earth benefit, from news reports presumably published by members of INN that contributed to those on average 1.4 additional prosecutions for political corruption estimated by Usher and Kim-Leffingwell (2022). We benefit even if we never heard about the news reports that contributed to those prosecutions. We benefit even if we have never heard of the news outlets that presumably did the investigative journalism behind those additional prosecutions. Why? Because on average those news reports likely deterred other incidents of political corruption, which likely contributed to broadly shared economic growth and the development of new technology that ultimately benefit the vast majority of humanity. Other aspects of this are documented in the research on the impact of [[w:news desert|news desert]]s, which we summarize next. === Costs increase in news deserts=== There's a growing body of research describing what happens when local newspapers die. Perhaps most important, a 2018 research report by Gao et al. reported that the death of a local newspaper was followed by … increases in local tax revenue, averaging $85 per human per year.<ref name = Gao2018>Gao et al. (2018).</ref> That $85 was roughly 13 hundredths of a percent of the 2019 US GDP. That's mentioned in the 2025-07-17 interview with [[Democratic delusions: Fix the media to fix democracy|Natalie Fenton about her new book, ''Democratic Delusions, How the Media Hollows out democracy and What We Can Do About It'']]. One of the most spectacular example of the cost of a news desert is the [[w:City of Bell scandal|Scandal of Bell, California]]. Their local newspaper died around 1999. Roughly a decade later the city was nearly bankrupt in spite of having property tax rates among the highest in the nation. An investigation by the ''[[w:Los Angeles Times|Los Angeles Times]]'' documented that the city manager had a compensation package worth $1.5 million a year, well over double that of the President of the United States. Other senior city officials were similarly well-remunerated. Some of the city officials went to jail over that. Did the city manager decide after 1999, "Wow: The watchdog is dead. Let's have a party"? Malfeasance also increases in business as pollution and workplace accidents increase as does the cost of capital, because investors know their money is not as secure without a local newspaper. That leads to a reduction in investments in new products, services and processes -- slowing economic growth. See "[[Local newspapers limit malfeasance]]", esp. Kim et al. (2021). And executive compensation in increases in nonprofits, so less of what people donate goes to the charitable purpose for which they donated, according to Felix et al. (2024). Also, voter participation and split-ticket voting decline, per Benton (2019) and other references discussed in "[[Information is a public good: Designing experiments to improve government]]". And the ultra-right does better, as noted in [[News from Germany 1900-1945 and implications for today]] and the section on "[[Information is a public good: Designing experiments to improve government#Previous research|Previous research]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]".<ref>Flößer (2024).</ref> The 0.13 percent of GDP savings estimated by Gao et al. (2018) is roughly $120 per human per year. With over 300 million humans in the U.S, that is roughly $40 billion nationwide. {| class="wikitable" |+ Table 1. Costs increase in news deserts |- ! Entity !! What !!Source |- | local government || costs incr. 0.13% of GDP || Gao et al. (2018) |- | local businesses || pollution & workplace accidents incr., innovation & econ growth decr. || Kim et al. (2021) |- | nonprofits || exec. compensation incr. || Felix et al. (2024) |- | rowspan=2 | elections | voter participation & split-ticket voting decl. || Benton (2019) |- | Ultra-right does better || Flößer (2024) |} === Government subsidies for news === John (1995) documented how in the first half of the nineteenth century the US had more independent newspaper publishers per million population than at any other time or place in human history.<ref>This is discussed in the 2025-06-08 [[Media concentration per Columbia History Professor Richard John|interview with him]], available on Wikiversity under [[:Category:Media reform to improve democracy]], accessed 2026-04-30.</ref> This encouraged literacy and limited political corruption, both of which helped [[The Great American Paradox|the early United States stay together and grow]] while contemporary [[w:New Spain|New Spain]] / [[w:Mexico|Mexico]], fractured, shrank, and stagnated economically. As documented with Figure 1 in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]], that growth catapulted the young United States into its current position of dominance in the international political economy, a position it has been losing since at least 1990 -- or since the Reagan Revolution began in 1981, according to the analysis in the chapter below on [[/Fox, the Great Depression, the Great Recession, and our future/]]. Other countries now have stronger democracies due in part to government subsidies for media in the range of 0.05 and 0.25 percent of GDP with a firewall that limits political interference in the content, according to Neff and Pickard (2024). Table 1 in "[[Information is a public good: Designing experiments to improve government]] compares media subsidies in various places with "other points of reference". McChesney and Nichols (2010, pp. 310-311, note 88) suggested that the relatively high rate of economic growth of the economy in the early US was due in part to postal subsidies under the US [[w:Postal Service Act|Postal Service Act]] of 1792.<ref>See also the Wikiversity article on "[[The Great American Paradox]]", accessed 2026-04-30.</ref> They estimated those subsidies at 0.21 percent of GDP. To improve the current political economy of the US, they recommended subsidies of 0.15 percent of GDP distributed to local news nonprofits on the basis of local elections.<ref>McChesney and Nichols (2021, 2022).</ref> The Wikipedia article on "[[Information is a public good: Designing experiments to improve government]]" documents how some jurisdictions can devote that much money to local news nonprofits by matching what they spend on accounting, advertising, and public relations.<ref>See the section on "[[Information is a public good: Designing experiments to improve government#Sampling units / experimental polities|Sampling units / experimental polities]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]", accessed 2026-04-30.</ref> Pickard (2023) describes three basic strategies for confronting concentrated commercial media power: (1) break them up, (2) regulate them, and (3) create non-commercial, public alternatives. A fourth possibility might be [[w:externality|a graduated tax on income and wealth]] in proportion to the threat that major corporations pose to democracy. One class of noncommercial alternatives that Pickard mentions is local multimedia / Public Media Centers (PMCs) with management split between local journalists and boards, e.g., selected at random from registered voters. A key here is to have the boards selected in a way that cannot be influenced by people with power, whether business or political elites. Picard recommends considering '''six discrete layers''' when discussing PMCs, each of which, he says, must be radically democratised: # funding, # governance, # ascertainment (to determine a community’s ''critical information needs''), # infrastructure (including universal broadband service), # algorithmic (e.g., not allowing companies like Google and Facebook to suppress indexing information the might challenge their hegemony of those markets, [[w:Deep web|treating them like pedophilia and the Islamic State]]), # engagement, involving local communities in making their own news and in communicating their own stories; this is paramount to building trust and the grassroots-level support that this new local journalistic model requires. All this needs to be managed in ways that provide substantive support to news deserts and underserved communities that have long been subjected to various kinds of informational redlining. This might be done by including the proposed PMCs within local libraries staffed by professional journalists, who provide training in media literacy in local schools for children and supervise students producing school newspapers. PMCs could host regular, e.g., monthly events, where local residents could share their concerns with journalist, who would use that input to help prioritize different issues for news coverage. Journalist could also coach local residents in how to research issues and collaborate with journalists in producing news reports that may be better researched and more relevant to local concerns than could be produced without such collaboration. Management of such PMCs might be split between journalists on staff and boards of, e.g., six members selected at random from voter registration rolls serving staggered terms of one year with a new member rotated in every 2 months. Another alternative that could be done in parallel with local PMCs calls for 200 journalists in each US Congressional district funded at $10 billion annually in 2022 dollars, which is just a little under 4 hundredths of one percent of GDP; if such allocations are expressed as fractions of a percent of GDP, they would grow naturally with the economy. (The nominal GDP for the US was roughly $26.1 trillion in 2022.<ref>Johnston and Williamson (2026).</ref> For 2026 it is estimated at $32.4 trillion.<ref>[[w:United States|United States]], accessed 2026-04-30.</ref>) A similar model is the [[w:BBC|BBC]]’s Local Democracy Reporting Service (LDRS), in which the BBC funds journalists to cover the work of local councils and other local public bodies, funded at £8 million per year, which is a little under 2 hundredths of a percent of the [[w:United Kingdom|UK]]'s GDP of £7.27 trillion.<ref>[[w:United Kingdom|United Kingdom]], accessed 2026-04-30.</ref> Pickard (2023) ended by saying, "Today we face a crossroads: technocracy and oligarchy from above or radical democracy and structural reform from below. ... [T]his is not just a journalism crisis: it is a democracy crisis." ==Table of Contents== *[[/Introduction/]] including an exercise, asking all to discuss perceptions of the settlement of ''[[w:Dominion Voting Systems v. Fox News Network|Dominion Voting Systems v. Fox News Network]]'' in a friendly supportive manner with humans with whom they may vehemently disagree, because the alternative could be killing humans over misunderstandings. ===Part I. The media and political economy=== # [[/The impact of the media on political economy since the time of the Pharaohs/]] describes how religious leaders in hierarchical societies prior to [[w:James VI and I|King James of the King James bible]] convinced commoners to live in poverty while giving increasing shares of what they produced so religious and secular elites could live in opulence. During the reign of King James, pamphlets and newspapers began to compete with the church for helping commoners understand their roles in society. This produced the Industrial Revolution and modern democracies. Media consolidation since World War II slowed, then reversed this trend. # [[/Fox, the Great Depression, the Great Recession, and our future/]] describes the unprecedented performance of the US political economy during the presidency of Franklin Roosevelt (FDR), insisting that much of what FDR achieved can be replicated, giving a media system that supports honest discussion of the available evidence. # [[/Media consolidation, social media, and political polarization/]] (Combine from McChesney and Nichols discussing the [[w:Postal Service Act|US Postal Service Act]] of 1792 with [[Media concentration per Columbia History Professor Richard John]], the section on "[[v:Information is a public good: Designing experiments to improve government#Threats from social media|Threats from social media]]" in "[[Information is a public good: Designing experiments to improve government]], and the comments by [[v:Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen that, "the shortest path to a click is anger or hate."]]. ===Part II. The media and war=== # [[/Deterrence without threat/]]: The historical record is clear: Nations that have prepared for war often got war, not peace. This happens for at least two reasons: First, some leaders cannot resist the temptation to use force inappropriately, sometimes clandestinely provoking others to do things that are then denounced as "unprovoked"; sometimes the media environment pushes them to do such. Alternatively, potential adversaries may believe -- or claim -- that you are actually preparing a first strike, and they must move preemptively or lose their ability to retaliate adequately. We can avoid these possibilities with three supportive policies: [a] Legislation that ''prohibits'' projecting force beyond our own borders. [b] Civilian-based defense training in nonviolent noncooperation like what helped Denmark survive Nazi occupation with minimal damage. And [c] a media system that penalizes rather than encourages a bellicose foreign policy. # [[/Responding to a nuclear attack/]]: The ''worst'' response to a nuclear attack would be a nuclear response: The death toll from the 1945 [[w:Atomic bombings of Hiroshima and Nagasaki|Atomic bombings of Hiroshima and Nagasaki]] was estimated at between 150,000 and a quarter of a million. By contrast, simulations of nuclear wars of different magnitudes estimated that between 4 and 95 percent of humanity around the world would starve to death if they did not die of something else sooner. The range depends on whether the war was "limited", e.g., between India and Pakistan, and massive between the US and Russia. (Also add material from [[Nuclear weapons and effective defense]]). # [[/Threats from excessive government secrecy/]] (draft in [https://sanjosepeace.org/restrict-secrecy-more-than-data-collection/ "Restrict secrecy more than data collection"], adding material from [https://kkfi.org/program-episodes/does-us-government-secrecy-threaten-national-security/ Connelly (2023) ''The Declassification Engine: What History Reveals About America's Top Secrets''], [[Wikipedia:Moynihan Commission on Government Secrecy]] and [[1998 Embassy bombings and September 11]]. # [[/Shouting fire in a crowded theater/|Shouting ''fire'' in a crowded theater]]: Legal concerns about "[[w:Shouting fire in a crowded theater|Shouting ''fire'' in a crowded theater]]" date, at least in large part, from the [[w:Supreme Court of the United States|US Supreme Court]] decisions in ''[[w:Schenck v. United States|Schenck v. United States]]'' (1919) and ''[[w: Brandenburg v. Ohio| Brandenburg v. Ohio]]'' (1969). In ''Schenck'' the Court ruled that the government had a right to imprison Schenck and others, because their distribution of fliers encouraging draft resistance presented a [[w:clear and present danger|clear and present danger]] to the efficacy of ongoing military activities during [[w:World War I|World War I]], then in progress. The Court in ''Brandenburg'' held that the government cannot punish inflammatory speech ''unless that speech is "directed to inciting or producing imminent lawless action and is likely to incite or produce such action".'' Some could argue that many uses of military force by the US and Israel since 1948 have violated international law, encouraged by biases in the major US media "directed to inciting or producing imminent lawless action", though it may not be feasible to convince a court of that. Still, it might be useful to simulate such a case in a mock trial like the 1966 [[w:Russell Tribunal|Russell Tribunal]].<ref>Andersen (2006) provides such documentation for several such uses of force. Andersen (2026) and Johnson (2026) organize evidence supporting such claims for the current [[w:Gaza war|Gaza war]], which began with [[w:October 7 attacks|Palestinian attacks 2023-10-07]]. Might, e.g., Palestinians -- or at least Palestinian Americans -- be able to sue the [[w:Anti-Defamation League|Anti-Defamation League]] (ADL), the [[w:AIPAC|American Israel Public Affairs Committee]] (AIPAC), and all the major media outlets in the US for inciting genocide in the current [[w:Gaza war|Gaza war]]? That history includes routine suppression of coverage by the major media especially in the US of routine denial of equal protection of Israeli laws to non-Jews in Israel and under Israeli occupation, including suppression of Israeli violence against nonviolent protestors peaceably assembling and petitioning for a redress of grievances combined with over reporting of Palestinian violence and unquestioning coverage of fraudulent claims of Palestinian violence by Israel and supporters. The suppressions included underreporting of Palestinian nonviolence such as the [[w:2018–2019 Gaza border protests|(2018-2019) Great March of Return]], and suppression of the grievances inspiring such nonviolence such as indefinite detention without charges of thousands of Palestinians, including children, routine destruction of Palestinian property by settlers, confiscation of Palestinian property at gunpoint, closing [[w:Gaza Strip|Gaza]] to international trade, and maintaining Gaza on starvation rations. These routine biases in reporting have been encouraged by charges that more honest reporting would be "[[w:Antisemitism|antisemetic]], according to the ADL and AIPAC. This denial of coverage thereby encouraged Israel to increase the rate of such violations until the [[w:October 7 attacks|2023-10-07 attacks on Israel from Gaza]] unleashed Israeli "retaliations" way out of proportion to the alleged provocation. Sucharov (2022) reported that 69% of American Jews opposed privileging Jews over non-Jews in Israel. Their support of Israel in the current Gaza war is consistent with the media biases documented by Johnson (2026) and others including Andersen (2006, 2026). Regarding whether Israel could achieve anything positive from this war, Samuelson (2025) is skeptical. He summarized quantitative analyses of 60 previous insurgencies. The results including the observation that it is exceedingly difficult to defeat an insurgency without responding to the grievances that support it without force ratios far beyond Israel's resources.</ref> ===Part III. Climate, immigrants, education, public health, and criminal justice=== # [[/Global warming/]] [Summarize research especially on conflicts of interest of major media in honestly reporting on this issue and the research on global warming itself and activities of groups concerned about this issue. Decompose into global population times CO2 equivalents per human.] # [[/Immigrants/]] [Summarize research documenting that [[w:Sanctuary city|sanctuary cities tend to have higher median incomes and no more crime than non-sanctuary jurisdictions]], and some studies report less crime. Moreover economists have documented that immigrants tend to be more entrepreneurial, overrepresented in patent applications, and generally increasing the rate of economic growth. See, e.g., Aghion et al. (2022) ''The power of creative destruction''; Aghion shared the 2025 Nobel Memorial Prize in Economics with two others.] # [[/Education/]] (draft in [[Invest in children]].) # [[/Public health/]] [Draft in [[UN public health data]] to be revised to be consistent with Bezruchka (2023, 2025).] # [[/Substance abuse and addictive behavior/]] (Research cited in "[[Wikipedia:War on drugs]]" insists that the US and the world would have fewer problems with substance abuse and addiction problems with 100 percent public funding for treatment programs and complete decriminalization of possession and use of retail quantities of addictive substances. We would also likely have fewer problems with immigrants, as that would make it harder for the US to intervene in the internal affairs of foreign countries funded off the books, as exposed in the [[w:Iran–Contra affair|Iran–Contra affair]]. See [[w:Alfred W. McCoy|Alfred W. McCoy]] (1972; 3rd ed. 2003) ''The politics of heroin''. Journalist [[w:Gary Webb|Gary Webb]] published similar claims that the US intervention in Nicaragua in the Iran-Contra Affair was funded in part by drug money. The story was officially retracted by the ''San José Mercury News'', and Webb allegedly killed himself with 2 bullets to the head. # [[/Criminal justice/]] (The section on "[[w:United States incarceration rate#Editorial policies of major media|Editorial policies of major media]]" in "[[Wikipedia:United States incarceration rate]]" cites research claiming that within the range range of experience in the US political economy since 1925, the incarceration rate is uncorrelated with crime: It's a function of the public's perception of crime, and that's a function of the media. That suggest that the US would be safer and more prosperous if incarceration policies were driving more by research than by editorial policies of the media. For example, there is also research that says that incarcerees who receive visits are less likely to recidivate, but that evidence is overlooked when convicts are incarcerated substantial distance from their family and friends and when the cost of phone services is substantially higher for incarcerees than among the general pubic. Also, it's known that better educated incarcerees are less likely to recidivate, but it's difficult and maybe impossible for many incarcerees to obtain education in prison.) # [[/Empower women and girls/]] [Cite research claiming that a primary restraint on population growth is empowering women and girls. Empowering women and girls is not just a matter of equity: It is also a means to reduce the threats of global warming, of increasing exposure to animal diseases and other problems that come with unrestrained population growth.] === Continuation === * [[/The evolving media literacy movement/]] to invite others to keep this book current with the evolving understanding of media literacy, how to encourage and promote it and the benefits of doing so. ==See also== * [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools]] ==Notes== {{reflist}} ==Bibliography== * <!--Daron Acemoğlu and Simon Johnson (2023) Power and Progress-->{{cite Q|Q125292212}} * <!--Robin Andersen (2006) A century of media, a century of war-->{{cite Q|Q138795568}} * <!--Robin Andersen (2026-06-02) The Complicit Lens: US Media Coverage of Israel’s Genocide in Gaza-->{{cite Q|Q138796307}} * <!--Perry Bacon Jr. (2022-10-17) "America Should Spend Billions to Revive Local News"-->{{cite Q|Q139594786}} * <!-- Joshua Benton (9 April 2019). "When local newspapers shrink, fewer people bother to run for mayor". Nieman Foundation for Journalism -->{{cite Q|Q63127216}} * <!--Stephen Bezruchka (2023) Inequality Kills Us All-->{{cite Q|Q136047815}} * <!--Stephen Bezruchka (2025) ''Born Sick in the USA''-->{{cite Q|Q138749292}} * <!--Renée DiResta (2024) Invisible Rulers: The People Who Turn Lies into Reality-->{{cite Q|Q135530439}} * <!--Robert Felix, Joshua A. Khavis, and Mikhail Pevzner (2024) "The effects of local newspaper closures on nonprofits’ executive compensation"-->{{cite Q|Q132730972}} * <!--Maxim Flößer (2024-03-06) "Keine Lokalzeitung -- mehr AfD", Kontext-->{{cite Q|Q125287792}} * <!--Pengjie Gao, Chang Lee, and Dermot Murphy (2018) "Financing Dies in Darkness? The Impact of Newspaper Closures on Public Finance"-->{{cite Q|Q55670016}} * <!--Spencer Graves (2024) "Wikipedia: The most democratic force on earth-->{{cite Q|Q137796922}} * <!--Spencer Graves and Bryan Bailey (2025) "We have to talk", blog at PeaceWorksKC.org-->{{cite Q|Q136126262}} * [[d:Q138038060|Dan Hind and Spencer Graves (2025) "Media Reform Coalition challenges anti-democratic media bias in the UK" on Wikiversity]]. * <!--Richard R. John (1995) Spreading the News: The American Postal System from Franklin to Morse-->{{cite Q|Q54641943}} * <!--Adam H. Johnson (2026-04-21) How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza-->{{cite Q|Q140073447}} * <!--Louis Johnston and Samuel H. Williamson, "What Was the U.S. GDP Then?" MeasuringWorth, 2026-->{{cite Q|Q56881105}} * <!-- Min Kim, Derrald Stice, Han Stice, and Roger M. White (2021) "Stop the presses! Or wait, we might need them: Firm responses to local newspaper closures and layoffs"-->{{cite Q|Q132459373}} * <!-- Robert W. McChesney; John Nichols (2010). The Death and Life of American Journalism (Bold Type Books) -->{{cite Q|Q104888067}}. * <!-- Robert W. McChesney; John Nichols (2021). "The Local Journalism Initiative: a proposal to protect and extend democracy". Columbia Journalism Review, 30 November 2021 -->{{cite Q|Q109978060}} * <!-- Robert W. McChesney; John Nichols (2022), To Protect and Extend Democracy, Recreate Local News Media (PDF), FreePress.net (updated 25 January 2022) -->{{cite Q|Q109978337|access-date=2024-06-23}} * <!--Alfred W. McCoy (2003-05-01) The politics of heroin : CIA complicity in the global drug trade : Afghanistan, Southeast Asia, Central America, Colombia-->{{cite Q|Q141317509}} * <!--Joel Mokyr (2017) A Culture of Growth: The Origins of the Modern Economy (Graz Schumpeter Lectures; Princeton University Press)-->{{cite Q|Q136118590}} * <!--Neff and Pickard (2024) "Funding Democracy: Public Media and Democratic Health in 33 Countries"-->{{cite Q|Q131468289}} * [[d:Q131398359|Victor Pickard (2020) ''Democracy without journalism? : confronting the misinformation society'' (Oxford U. Pr.)]]. * <!-- Victor Pickard (2023-05-12) "Another Media System is Possible: Ripping Open the Overton Window, from Platforms to Public Broadcasting"-->{{cite Q|Q131398460}} * <!--Doug Samuelson (2025) Assessing Israel’s Approach in Gaza-->{{cite Q|Q138843324}} * [[d:Q138037937|Dean Starkman and Spencer Graves (2025) "Dean Starkman and the watchdog that didn't bark anglais" on Wikiversity]]. * <!--Mira Sucharov (2022) Do American Jews Really Know What 'Zionist' Means?-->{{cite Q|Q125903777}} * [[d:Q134715465|Nikki Usher and Sanghoon Kim-Leffingwell (2022) "How Loud Does the Watchdog Bark? A Reconsideration of Local Journalism, News Non-profits, and Political Corruption", ''SSRN Electronic Journal'']]. * [[d:Q61013892|Horacio Verbitsky (1997) ''Un mundo sin periodistas'' (in Spanish: A world without journalists; Editorial Sudamericana)]]. [[Category:Communication]] [[Category:Political science]] [[Category:Law]] [[Category:Psychology]] [[Category:Sociology]] [[Category:Education]] [[Category:Economics]] [[Category:Media Literacy and You]] [[Category:Freedom and abundance]] <!-- https://en.wikiversity.org/wiki/Category_Review --> okcxi45cdr837ibjxkywxg44a86udqa 2835373 2835372 2026-10-01T17:29:12Z DavidMCEddy 218607 wdsmth 2835373 wikitext text/x-wiki [[File:Pharoah - James VI and I - Trump.png|thumb|Religious and media leaders from the time of the Pharaohs convinced common folk to give increasing shares of what they produced to elites.]] :''This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.'' == Invitation to edit this book == You, dear reader, are invited to contribute questions, ideas and citations to support or refute claims made in this book possibly adding chapters. Wikiversity like other Wikimedia Foundation Projects invites humans to [[w:Wikipedia:Be bold|“be bold but not reckless,”]] while writing from a [[Wikiversity:Disclosures|neutral point of view]], [[Wikiversity:Cite sources|citing credible sources]]. Others are invited to change or revert what you wrote. What stays tends to be written from a neutral point of view citing credible sources. If someone reverts your edit or you have a question, take it to the ''[[Wikiversity:FAQ|''''“Discuss”'''' page]]'' associated with the specific Wikiversity page most related to your concerns. Those who teach media literacy are encouraged to invite their students to debate and revise the contents of this book. Doing so would build on a tradition of [[:w:Wikipedia:Student assignments|instructors requiring students to edit wikipedia article(s).]] Editing [[:w:Wikipedia|Wikipedia]] and other [[:w:Wikimedia Foundation|Wikimedia Foundation]] projects like this book is itself an exercise in media literacy: :''Central tenets of media literacy might include writing from a neutral point of view citing credible sources and engaging others, some of whom may disagree, in civil, supportive conversations about what can and cannot be said based on a reasonable evaluation of the available evidence. Wikimedia rules invite contributors to do just that, encouraging them to “be bold but not reckless,” contributing revisions written from a neutral point of view, citing credible sources -- and raising other questions and concerns on the ''''“Discuss”'''' page associated with the specific Wikiversity page most related to your concerns, as mentioned above.''<ref>For more on this, see Graves (2024).</ref> == Text and self-help book and point of discuss == This book is intended both as a text and self-help book and as a point of discussion considering four levels of media literacy: :1. '''Think before you share''': Follow the money. Every media organization sells changes in audience behaviors to those who control much of their money. Major media everywhere promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to convince the public to give increasing shares of what they produce to elites to "protect them from designated evil others." To counter this, DiResta (2024, p. 335) recommends, "Think before you share." :2. '''Look for information to contradict preconceptions''' (Disconfirmation bias): [[w:Information is a public good: Designing experiments to improve government#Previous research|Virtually everyone]] (a) thinks they know more than they do ([[w:Overconfidence effect|overconfidence effect]]), and (b) prefers information and sources consistent with preconceptions ([[w:Confirmation bias|confirmation bias]]). The major media everywhere exploit this to please those who control most of the money for the media. Humans can counter this by searching for sources to help us understand our designated enemies. ''If we cannot explain circumstances under which we could see ourselves doing what we see our designated enemies doing, we have not looked hard enough.'' :3. '''Talk''': Push ourselves to have friendly supportive conversations with others with whom we may vehemently disagree, seeking common ground, agreeing to disagree agreeably where we differ, and building collaboration on areas of common concern.<ref>Graves and Bailey (2025).</ref> :4. '''Teach''': Humans who develop skills in the first three levels can leverage that knowledge in helping others acquire those skills. If each one teaches two<ref>"[[:w:Each one teach one|Each one teach one]]" is an African-American proverb from the time of legalized slavery. However, if each one teaches only one, the growth in literacy will only be linear. Having "each one teaching two", on average, unleashes the power of doubling and [[:w:exponential growth|exponential growth]], which has the potential of educating the entirety of humanity in a reasonable period of time -- namely after 33 doublings starting from one.</ref> in a certain period of time, that time period becomes a [[:w:Doubling time|doubling time]]. Ten doublings is a thousand -- actually 1,024 to be precise.<ref>2 time 2 = 4 times 2 = 8 times 2 = 16 times 2 = 32 times 2 = 64 times 2 = 128 times 2 = 256 times 2 = 512 times 2 = 1024: That's 10 doublings, as anyone with a modest understanding of modern digital [[:w:computer|computer]]s will tell you.</ref> Twenty doublings become a million. Thirty doublings become a billion. Three more doublings become 8 billion, the [[:w:World population|world population]] as of approximately 2022-11-15.<ref>This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.</ref> Many organizations, including several United Nations agencies and the [[Yonty Friesem on media education|Media Education Lab]], have been working on [[w:media literacy|media literacy]] for decades and have trained many.<ref>''[[Wikibooks:Antiracist Activism for Teachers and Students]]'' includes a chapter on [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools|Media Literacy In Schools]].</ref> This book is being written hoping to increase the effectiveness and accelerate the rate of growth in media literacy and thereby accelerate progress against many of the most pressing issues facing humanity today.<ref>[[w:Nolan Higdon|Nolan Higdon]] and Spencer Graves discussed marketing media literacy in a "[[:Category:Media reform to improve democracy|Media & Democracy]]" episode on, "[[Media literacy and why you should care]]".</ref> Much of this book is a [[w:Monograph|research monograph]] summarizing research that seems to have been underreported by the major media to avoid offending people who control most of the money for the media. These research results seem to be central to major political divisions. Each chapter ends in exercises to help the reader practice media literacy skills and have fun doing it. Remember: :''I am entitled to my [[Wiktionary:cockamamie|cockamamie]] ideas, and you are entitled to yours.'' Humor is important but must be offered in a way that does not offend others. If others are offended, they may be less interested in dialogue. The term "cockamamie" is used here, hoping that this style of [[w:Self-deprecation|self-deprecation]] might be more inviting for dialogue. ''Never say, "You're wrong." Instead, ask, "May I offer a contrary perspective?" Or "May I share with you another view that I've heard?"'' Much of the information in this book seems to have been largely overlooked and perhaps suppressed, apparently because it would either offend people who control substantial portions of the money for the media our would increase the cost of producing news; see the brief discussion of conflicts of interest by the major media in the next "Key claims" section. ==Key claims== * ''Primary drivers of every major conflict include differences between the media or difference in interpretation that the different parties find credible''. :-- This works, because everything we think we know is coded in systems of connections between neurons in our brains. These systems are more unique than fingerprints and evolve over time. The words we use do not mean the same to two different humans nor even to the same human at different points in time. In many cases these differences are inconsequential. ''Sometimes they are fatal.''<ref>Graves and Bailey (2026).</ref> :-- ''[[w:Social constructionism|Show me someone who knows the truth]], and I will show you someone who is dangerous'' -- especially during war or any other situation where humans may be moved to violence encouraged by their belief system.<ref>[[w:Collateral damage|Collateral damage]] that "they" commit proves to "us" that "they" are subhuman or at best criminally misled and must be resisted by any means necessary. By contrast, collateral damage that "we" commit is unfortunate but necessary.</ref> * ''The major media everywhere have [[w:Conflict of interest|conflicts of interest ]] in honestly reporting on [[v:Information is a public good per communications prof Pickard|anything that might offend anyone who controls large portions of the money for the media]].''<ref>Pickard and Graves (2025), accessed 2026-02-08; Pickard (2020).</ref> :--[[v:Media Reform Coalition challenges anti-democratic media bias in the UK|British journalist and media reform advocate Dan Hind]] said that the content produced by the [[w:BBC|BBC]] was frivolous, soap opera stuff, because leading media personalities know very little about issues of substance and believe "they might get in trouble if" they produced anything serious. Similar analyses seem to apply to the major media everywhere<ref>Hind and Graves (2025), accessed 2026-02-09.</ref> but may not apply to non-profit and local media, which seem more likely to produce [[w:Investigative journalism|investigative]] / [[v:Dean Starkman and the watchdog that didn't bark|accountability journalism]]:<ref>Usher and Kim-Leffingwell (2022); see also Starkman and Graves (2025), accessed 2026-02-09.</ref> [[w:Watchdog journalism|Watchdogs]] tend to protect the people who feed them. Argentine journalist [[w:Horacio Verbitsky|Horacio Verbitsky]] said, "Journalism is disseminating information that someone does not want known; the rest is [[w:propaganda|propaganda]]."<ref>p. 16 in Verbitsky (1997); English translation from [[Wikiquote:Horacio Verbitsky]], accessed 2026-02-09.</ref> * ''The major media everywhere create the stage upon which politicians read their lines.'' :-- Major media promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to make it easier for elites to pick everyone else's pockets. This is particularly effective with for-profit social media, which make money herding their audience into echo chambers, where erroneous preconceptions are reinforced, increasing political polarization and violence. [[Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen said]], "The shortest path to a click is anger or hate." A leading expert on for-profit social media is Renée DiResta,<ref>DiResta (2024).</ref> whose research documents how lies spread on social media threaten public health and prepped a small army of humans throughout the 2020 US presidential election cycle to believe that there were major deficiencies in the integrity of US election procedures. When Trump lost, he was able to recruit [[w:January 6 United States Capitol attack|a crowd to attack the capitol on January 6, 2021]]. Social media influencers made so much money spreading lies that it seemed profitable for them to file frivolous lawsuits ([[w:Strategic lawsuit against public participation|SLAPP]]), hoping that DiResta's legal bills would convince her to stop trying to expose their lies. After Republicans regained control of the US House in 2022, they subpoenaed her, claiming she had taken orders from the "[[w:Deep state|deep state]]" to tell Facebook to censor conservatives. [[Managing the good and the evils of social media|When interviewed for ''Media & Democracy'', she reported legal bills of $7 million]]. :-- The social psychology behind this phenomenon exploits especially [[w:confirmation bias|confirmation bias]]. It has contributed to [[Media Literacy and You/Media consolidation, social media, and political polarization|the dramatic increase in political polarization and violence worldwide]], especially since the end of the [[w:Fairness doctrine|Fairness doctrine]] in 1987. :-- Democracy may be best protected by local news nonprofits, managed jointly by journalists and boards selected at random from registered voters, according to Pickard (2023), discussed in the section below on "[[Media Literacy and You#Government subsidies for news|Government subsidies for news]]". :-- Their selection of acceptable topics for news and entertainment create and maintain the "[[w:Overton window|Overton window]]", which is the range of acceptable political discourse. For example, in early 1964, US President [[w:Lyndon B. Johnson|Lyndon Johnson]] understood that he could lose the 1964 presidential election that year if he were seen to be soft on communism. His response was to clandestinely provoke an attack on US naval vessels in the Gulf of Tonkin, which he could then denounce as "unprovoked". During a dark and stormy night 1964-08-04 the [[w:USS Maddox (DD-731)|USS ''Maddox'']] and [[w:USS Turner Joy|''Turner Joy'']] spent a couple of hours "defending themselves" against radar snow, then [[w:Gulf of Tonkin incident|reported that they had sunk two attacking North Vietnamese torpedo boats]]; subsequent investigations found no evidence of the reported attacks. That incident was used to justify the [[w:Gulf of Tonkin Resolution|Gulf of Tonkin Resolution]], with only two dissenting votes in the US Congress: Those two dissenters were defeated in their next reelection campaigns, illustrating the point that ::''the major media create the environment in which many politicians cannot get elected without betraying the nation.'' :-- Nick Hart,<ref name=Hart><!--Nick Hart-->{{cite Q|Q135663983}}</ref> President and CEO of the Data Foundation,<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> noted that President Trump in his first term signed the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] of 2019, which was bipartisan legislation ostensibly mandating evidence-informed public policy.<ref>Hart mentioned the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] when he was interviewed for [[Evidence-informed public policy|"Media & Democracy" 2025-07-31]].</ref> Tragically, the record since 2019 suggests that, ::''The US Congress is rarely allowed to consider solid research suppressed by the major media.'' * ''The development of technology is never neutral in its impact on inequality but is driven to benefit people with power.''<ref>Acemoglu and Johnson (2023)</ref>. :-- [[Media Literacy and You/The impact of the media on political economy since the time of the Pharaohs|Improvements in agricultural technology from pre-history to the time of King James of the King James bible were managed to benefit elites.]] Then pamphlets and newspapers began to appear, the head of state stopped granting as many monopolies, and commoners began getting permission to become entrepreneurs. That transformed economic stagnation into growth in GDP per capita adjusted for inflation, initiating the [[w:Industrial Revolution|Industrial Revolution]], as documented in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]]. It also led to increasing inequality until organized labor got enough political power to demand and get a bigger share of the fruits of their labors. :--[[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|In the US those benefits peaked during the Great Depression]], when the standard conservative mantra that blames the poor for their poverty did not sell newspapers. US President Franklin Roosevelt taxed the ultra-wealthy like they had never been taxed before or since, and dramatically reduced inequality, which continued to decline until increasing concentration of ownership of the media ushered in a new era of increasing inequality starting with the presidency of Ronald Reagan. :-- [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future#Role of the media|Acemoglu and Johnson insist that technology, including artificial intelligence, can be developed to benefit all. However, but it will not happen without action by the poor and middle class as follows]]: :# Alter the narrative, :# Build countervailing powers [like organized labor], and :# Develop technical, regulatory, and policy solutions to tackle specific aspects of technology’s social bias.<ref>Acemoglu and Johnson (2023, ch. 11).</ref> :-- For more on this, see, e.g., the chapter on [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|Fox, the Great Depression, the Great Recession, and our future]]. === The value of noncommercial news outlets === Some of the problems with the media and their contributions to increasing political polarization and violence are documented in the research summary on "[[Information is a public good: Designing experiments to improve government]]" and in the podcast series available on Wikiversity under "[[:Category:Media reform to improve democracy]]" with leading experts discussing their recommendations. One of the most compelling of the references discussed in that podcast series is Usher and Kim-Leffingwell (2022), who tallied all the federal prosecutions for political corruption in each of the 94 [[w:United States federal judicial district|US federal court district]]s between 2003 and 2019. During that period, the number of journalists in the US fell by a factor of roughly 3 -- between 60 and 70 percent. They found no statistically significant impact on federal prosecutions for political corruption of that decline in the number of journalists. However, each member of the [[w:Institute for Nonprofit News|Institute for Nonprofit News]] (INN) in a federal court district in one year was associated with on average 1.4 additional prosecutions for political corruption the following year. Since federal prosecutions for political corruption averaged roughly 10 per federal court district per year during that period. each member of INN in a federal court district one year was associated with a 14 percent increase in federal prosecutions the following year. This suggests that the major media outlets that had so dramatically reduced their staffs had not substantively reduced the amount of investigative journalism they did. If we assume that the people prosecuted for political corruption also control substantive advertising budgets, then the major media outlets have conflicts of interest in honestly reporting on such. They may report on it if some other organization like a member of INN does the research and they are threatened with a loss of audience from not reporting on it. :'''''Major point''''': You and I benefit, the vast majority of humans on earth benefit, from news reports presumably published by members of INN that contributed to those on average 1.4 additional prosecutions for political corruption estimated by Usher and Kim-Leffingwell (2022). We benefit even if we never heard about the news reports that contributed to those prosecutions. We benefit even if we have never heard of the news outlets that presumably did the investigative journalism behind those additional prosecutions. Why? Because on average those news reports likely deterred other incidents of political corruption, which likely contributed to broadly shared economic growth and the development of new technology that ultimately benefit the vast majority of humanity. Other aspects of this are documented in the research on the impact of [[w:news desert|news desert]]s, which we summarize next. === Costs increase in news deserts=== There's a growing body of research describing what happens when local newspapers die. Perhaps most important, a 2018 research report by Gao et al. reported that the death of a local newspaper was followed by … increases in local tax revenue, averaging $85 per human per year.<ref name = Gao2018>Gao et al. (2018).</ref> That $85 was roughly 13 hundredths of a percent of the 2019 US GDP. That's mentioned in the 2025-07-17 interview with [[Democratic delusions: Fix the media to fix democracy|Natalie Fenton about her new book, ''Democratic Delusions, How the Media Hollows out democracy and What We Can Do About It'']]. One of the most spectacular example of the cost of a news desert is the [[w:City of Bell scandal|Scandal of Bell, California]]. Their local newspaper died around 1999. Roughly a decade later the city was nearly bankrupt in spite of having property tax rates among the highest in the nation. An investigation by the ''[[w:Los Angeles Times|Los Angeles Times]]'' documented that the city manager had a compensation package worth $1.5 million a year, well over double that of the President of the United States. Other senior city officials were similarly well-remunerated. Some of the city officials went to jail over that. Did the city manager decide after 1999, "Wow: The watchdog is dead. Let's have a party"? Malfeasance also increases in business as pollution and workplace accidents increase as does the cost of capital, because investors know their money is not as secure without a local newspaper. That leads to a reduction in investments in new products, services and processes -- slowing economic growth. See "[[Local newspapers limit malfeasance]]", esp. Kim et al. (2021). And executive compensation in increases in nonprofits, so less of what people donate goes to the charitable purpose for which they donated, according to Felix et al. (2024). Also, voter participation and split-ticket voting decline, per Benton (2019) and other references discussed in "[[Information is a public good: Designing experiments to improve government]]". And the ultra-right does better, as noted in [[News from Germany 1900-1945 and implications for today]] and the section on "[[Information is a public good: Designing experiments to improve government#Previous research|Previous research]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]".<ref>Flößer (2024).</ref> The 0.13 percent of GDP savings estimated by Gao et al. (2018) is roughly $120 per human per year. With over 300 million humans in the U.S, that is roughly $40 billion nationwide. {| class="wikitable" |+ Table 1. Costs increase in news deserts |- ! Entity !! What !!Source |- | local government || costs incr. 0.13% of GDP || Gao et al. (2018) |- | local businesses || pollution & workplace accidents incr., innovation & econ growth decr. || Kim et al. (2021) |- | nonprofits || exec. compensation incr. || Felix et al. (2024) |- | rowspan=2 | elections | voter participation & split-ticket voting decl. || Benton (2019) |- | Ultra-right does better || Flößer (2024) |} === Government subsidies for news === John (1995) documented how in the first half of the nineteenth century the US had more independent newspaper publishers per million population than at any other time or place in human history.<ref>This is discussed in the 2025-06-08 [[Media concentration per Columbia History Professor Richard John|interview with him]], available on Wikiversity under [[:Category:Media reform to improve democracy]], accessed 2026-04-30.</ref> This encouraged literacy and limited political corruption, both of which helped [[The Great American Paradox|the early United States stay together and grow]] while contemporary [[w:New Spain|New Spain]] / [[w:Mexico|Mexico]], fractured, shrank, and stagnated economically. As documented with Figure 1 in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]], that growth catapulted the young United States into its current position of dominance in the international political economy, a position it has been losing since at least 1990 -- or since the Reagan Revolution began in 1981, according to the analysis in the chapter below on [[/Fox, the Great Depression, the Great Recession, and our future/]]. Other countries now have stronger democracies due in part to government subsidies for media in the range of 0.05 and 0.25 percent of GDP with a firewall that limits political interference in the content, according to Neff and Pickard (2024). Table 1 in "[[Information is a public good: Designing experiments to improve government]] compares media subsidies in various places with "other points of reference". McChesney and Nichols (2010, pp. 310-311, note 88) suggested that the relatively high rate of economic growth of the economy in the early US was due in part to postal subsidies under the US [[w:Postal Service Act|Postal Service Act]] of 1792.<ref>See also the Wikiversity article on "[[The Great American Paradox]]", accessed 2026-04-30.</ref> They estimated those subsidies at 0.21 percent of GDP. To improve the current political economy of the US, they recommended subsidies of 0.15 percent of GDP distributed to local news nonprofits on the basis of local elections.<ref>McChesney and Nichols (2021, 2022).</ref> The Wikipedia article on "[[Information is a public good: Designing experiments to improve government]]" documents how some jurisdictions can devote that much money to local news nonprofits by matching what they spend on accounting, advertising, and public relations.<ref>See the section on "[[Information is a public good: Designing experiments to improve government#Sampling units / experimental polities|Sampling units / experimental polities]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]", accessed 2026-04-30.</ref> Pickard (2023) describes three basic strategies for confronting concentrated commercial media power: (1) break them up, (2) regulate them, and (3) create non-commercial, public alternatives. A fourth possibility might be [[w:externality|a graduated tax on income and wealth]] in proportion to the threat that major corporations pose to democracy. One class of noncommercial alternatives that Pickard mentions is local multimedia / Public Media Centers (PMCs) with management split between local journalists and boards, e.g., selected at random from registered voters. A key here is to have the boards selected in a way that cannot be influenced by people with power, whether business or political elites. Picard recommends considering '''six discrete layers''' when discussing PMCs, each of which, he says, must be radically democratised: # funding, # governance, # ascertainment (to determine a community’s ''critical information needs''), # infrastructure (including universal broadband service), # algorithmic (e.g., not allowing companies like Google and Facebook to suppress indexing information the might challenge their hegemony of those markets, [[w:Deep web|treating them like pedophilia and the Islamic State]]), # engagement, involving local communities in making their own news and in communicating their own stories; this is paramount to building trust and the grassroots-level support that this new local journalistic model requires. All this needs to be managed in ways that provide substantive support to news deserts and underserved communities that have long been subjected to various kinds of informational redlining. This might be done by including the proposed PMCs within local libraries staffed by professional journalists, who provide training in media literacy in local schools for children and supervise students producing school newspapers. PMCs could host regular, e.g., monthly events, where local residents could share their concerns with journalist, who would use that input to help prioritize different issues for news coverage. Journalist could also coach local residents in how to research issues and collaborate with journalists in producing news reports that may be better researched and more relevant to local concerns than could be produced without such collaboration. Management of such PMCs might be split between journalists on staff and boards of, e.g., six members selected at random from voter registration rolls serving staggered terms of one year with a new member rotated in every 2 months. Another alternative that could be done in parallel with local PMCs calls for 200 journalists in each US Congressional district funded at $10 billion annually in 2022 dollars, which is just a little under 4 hundredths of one percent of GDP; if such allocations are expressed as fractions of a percent of GDP, they would grow naturally with the economy. (The nominal GDP for the US was roughly $26.1 trillion in 2022.<ref>Johnston and Williamson (2026).</ref> For 2026 it is estimated at $32.4 trillion.<ref>[[w:United States|United States]], accessed 2026-04-30.</ref>) A similar model is the [[w:BBC|BBC]]’s Local Democracy Reporting Service (LDRS), in which the BBC funds journalists to cover the work of local councils and other local public bodies, funded at £8 million per year, which is a little under 2 hundredths of a percent of the [[w:United Kingdom|UK]]'s GDP of £7.27 trillion.<ref>[[w:United Kingdom|United Kingdom]], accessed 2026-04-30.</ref> Pickard (2023) ended by saying, "Today we face a crossroads: technocracy and oligarchy from above or radical democracy and structural reform from below. ... [T]his is not just a journalism crisis: it is a democracy crisis." ==Table of Contents== *[[/Introduction/]] including an exercise, asking all to discuss perceptions of the settlement of ''[[w:Dominion Voting Systems v. Fox News Network|Dominion Voting Systems v. Fox News Network]]'' in a friendly supportive manner with humans with whom they may vehemently disagree, because the alternative could be killing humans over misunderstandings. ===Part I. The media and political economy=== # [[/The impact of the media on political economy since the time of the Pharaohs/]] describes how religious leaders in hierarchical societies prior to [[w:James VI and I|King James of the King James bible]] convinced commoners to live in poverty while giving increasing shares of what they produced so religious and secular elites could live in opulence. During the reign of King James, pamphlets and newspapers began to compete with the church for helping commoners understand their roles in society. This produced the Industrial Revolution and modern democracies. Media consolidation since World War II slowed, then reversed this trend. # [[/Fox, the Great Depression, the Great Recession, and our future/]] describes the unprecedented performance of the US political economy during the presidency of Franklin Roosevelt (FDR), insisting that much of what FDR achieved can be replicated, giving a media system that supports honest discussion of the available evidence. # [[/Media consolidation, social media, and political polarization/]] (Combine from McChesney and Nichols discussing the [[w:Postal Service Act|US Postal Service Act]] of 1792 with [[Media concentration per Columbia History Professor Richard John]], the section on "[[v:Information is a public good: Designing experiments to improve government#Threats from social media|Threats from social media]]" in "[[Information is a public good: Designing experiments to improve government]], and the comments by [[v:Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen that, "the shortest path to a click is anger or hate."]]. ===Part II. The media and war=== # [[/Deterrence without threat/]]: The historical record is clear: Nations that have prepared for war often got war, not peace. This happens for at least two reasons: First, some leaders cannot resist the temptation to use force inappropriately, sometimes clandestinely provoking others to do things that are then denounced as "unprovoked"; sometimes the media environment pushes them to do such. Alternatively, potential adversaries may believe -- or claim -- that you are actually preparing a first strike, and they must move preemptively or lose their ability to retaliate adequately. We can avoid these possibilities with three supportive policies: [a] Legislation that ''prohibits'' projecting force beyond our own borders. [b] Civilian-based defense training in nonviolent noncooperation like what helped Denmark survive Nazi occupation with minimal damage. And [c] a media system that penalizes rather than encourages a bellicose foreign policy. # [[/Responding to a nuclear attack/]]: The ''worst'' response to a nuclear attack would be a nuclear response: The death toll from the 1945 [[w:Atomic bombings of Hiroshima and Nagasaki|Atomic bombings of Hiroshima and Nagasaki]] was estimated at between 150,000 and a quarter of a million. By contrast, simulations of nuclear wars of different magnitudes estimated that between 4 and 95 percent of humanity around the world would starve to death if they did not die of something else sooner. The range depends on whether the war was "limited", e.g., between India and Pakistan, and massive between the US and Russia. (Also add material from [[Nuclear weapons and effective defense]]). # [[/Threats from excessive government secrecy/]] (draft in [https://sanjosepeace.org/restrict-secrecy-more-than-data-collection/ "Restrict secrecy more than data collection"], adding material from [https://kkfi.org/program-episodes/does-us-government-secrecy-threaten-national-security/ Connelly (2023) ''The Declassification Engine: What History Reveals About America's Top Secrets''], [[Wikipedia:Moynihan Commission on Government Secrecy]] and [[1998 Embassy bombings and September 11]]. # [[/Shouting fire in a crowded theater/|Shouting ''fire'' in a crowded theater]]: Legal concerns about "[[w:Shouting fire in a crowded theater|Shouting ''fire'' in a crowded theater]]" date, at least in large part, from the [[w:Supreme Court of the United States|US Supreme Court]] decisions in ''[[w:Schenck v. United States|Schenck v. United States]]'' (1919) and ''[[w: Brandenburg v. Ohio| Brandenburg v. Ohio]]'' (1969). In ''Schenck'' the Court ruled that the government had a right to imprison Schenck and others, because their distribution of fliers encouraging draft resistance presented a [[w:clear and present danger|clear and present danger]] to the efficacy of ongoing military activities during [[w:World War I|World War I]], then in progress. The Court in ''Brandenburg'' held that the government cannot punish inflammatory speech ''unless that speech is "directed to inciting or producing imminent lawless action and is likely to incite or produce such action".'' Some could argue that many uses of military force by the US and Israel since 1948 have violated international law, encouraged by biases in the major US media "directed to inciting or producing imminent lawless action", though it may not be feasible to convince a court of that. Still, it might be useful to simulate such a case in a mock trial like the 1966 [[w:Russell Tribunal|Russell Tribunal]].<ref>Andersen (2006) provides such documentation for several such uses of force. Andersen (2026) and Johnson (2026) organize evidence supporting such claims for the current [[w:Gaza war|Gaza war]], which began with [[w:October 7 attacks|Palestinian attacks 2023-10-07]]. Might, e.g., Palestinians -- or at least Palestinian Americans -- be able to sue the [[w:Anti-Defamation League|Anti-Defamation League]] (ADL), the [[w:AIPAC|American Israel Public Affairs Committee]] (AIPAC), and all the major media outlets in the US for inciting genocide in the current [[w:Gaza war|Gaza war]]? That history includes routine suppression of coverage by the major media especially in the US of routine denial of equal protection of Israeli laws to non-Jews in Israel and under Israeli occupation, including suppression of Israeli violence against nonviolent protestors peaceably assembling and petitioning for a redress of grievances combined with over reporting of Palestinian violence and unquestioning coverage of fraudulent claims of Palestinian violence by Israel and supporters. The suppressions included underreporting of Palestinian nonviolence such as the [[w:2018–2019 Gaza border protests|(2018-2019) Great March of Return]], and suppression of the grievances inspiring such nonviolence such as indefinite detention without charges of thousands of Palestinians, including children, routine destruction of Palestinian property by settlers, confiscation of Palestinian property at gunpoint, closing [[w:Gaza Strip|Gaza]] to international trade, and maintaining Gaza on starvation rations. These routine biases in reporting have been encouraged by charges that more honest reporting would be "[[w:Antisemitism|antisemetic]], according to the ADL and AIPAC. This denial of coverage thereby encouraged Israel to increase the rate of such violations until the [[w:October 7 attacks|2023-10-07 attacks on Israel from Gaza]] unleashed Israeli "retaliations" way out of proportion to the alleged provocation. Sucharov (2022) reported that 69% of American Jews opposed privileging Jews over non-Jews in Israel. Their support of Israel in the current Gaza war is consistent with the media biases documented by Johnson (2026) and others including Andersen (2006, 2026). Regarding whether Israel could achieve anything positive from this war, Samuelson (2025) is skeptical. He summarized quantitative analyses of 60 previous insurgencies. The results including the observation that it is exceedingly difficult to defeat an insurgency without responding to the grievances that support it without force ratios far beyond Israel's resources.</ref> ===Part III. Climate, immigrants, education, public health, and criminal justice=== # [[/Global warming/]] [Summarize research especially on conflicts of interest of major media in honestly reporting on this issue and the research on global warming itself and activities of groups concerned about this issue. Decompose into global population times CO2 equivalents per human.] # [[/Immigrants/]] [Summarize research documenting that [[w:Sanctuary city|sanctuary cities tend to have higher median incomes and no more crime than non-sanctuary jurisdictions]], and some studies report less crime. Moreover economists have documented that immigrants tend to be more entrepreneurial, overrepresented in patent applications, and generally increasing the rate of economic growth. See, e.g., Aghion et al. (2022) ''The power of creative destruction''; Aghion shared the 2025 Nobel Memorial Prize in Economics with two others.] # [[/Education/]] (draft in [[Invest in children]].) # [[/Public health/]] [Draft in [[UN public health data]] to be revised to be consistent with Bezruchka (2023, 2025).] # [[/Substance abuse and addictive behavior/]] (Research cited in "[[Wikipedia:War on drugs]]" insists that the US and the world would have fewer problems with substance abuse and addiction problems with 100 percent public funding for treatment programs and complete decriminalization of possession and use of retail quantities of addictive substances. We would also likely have fewer problems with immigrants, as that would make it harder for the US to intervene in the internal affairs of foreign countries funded off the books, as exposed in the [[w:Iran–Contra affair|Iran–Contra affair]]. See [[w:Alfred W. McCoy|Alfred W. McCoy]] (1972; 3rd ed. 2003) ''The politics of heroin''. Journalist [[w:Gary Webb|Gary Webb]] published similar claims that the US intervention in Nicaragua in the Iran-Contra Affair was funded in part by drug money. The story was officially retracted by the ''San José Mercury News'', and Webb allegedly killed himself with 2 bullets to the head. # [[/Criminal justice/]] (The section on "[[w:United States incarceration rate#Editorial policies of major media|Editorial policies of major media]]" in "[[Wikipedia:United States incarceration rate]]" cites research claiming that within the range range of experience in the US political economy since 1925, the incarceration rate is uncorrelated with crime: It's a function of the public's perception of crime, and that's a function of the media. That suggest that the US would be safer and more prosperous if incarceration policies were driving more by research than by editorial policies of the media. For example, there is also research that says that incarcerees who receive visits are less likely to recidivate, but that evidence is overlooked when convicts are incarcerated substantial distance from their family and friends and when the cost of phone services is substantially higher for incarcerees than among the general pubic. Also, it's known that better educated incarcerees are less likely to recidivate, but it's difficult and maybe impossible for many incarcerees to obtain education in prison.) # [[/Empower women and girls/]] [Cite research claiming that a primary restraint on population growth is empowering women and girls. Empowering women and girls is not just a matter of equity: It is also a means to reduce the threats of global warming, of increasing exposure to animal diseases and other problems that come with unrestrained population growth.] === Continuation === * [[/The evolving media literacy movement/]] to invite others to keep this book current with the evolving understanding of media literacy, how to encourage and promote it and the benefits of doing so. ==See also== * [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools]] ==Notes== {{reflist}} ==Bibliography== * <!--Daron Acemoğlu and Simon Johnson (2023) Power and Progress-->{{cite Q|Q125292212}} * <!--Robin Andersen (2006) A century of media, a century of war-->{{cite Q|Q138795568}} * <!--Robin Andersen (2026-06-02) The Complicit Lens: US Media Coverage of Israel’s Genocide in Gaza-->{{cite Q|Q138796307}} * <!--Perry Bacon Jr. (2022-10-17) "America Should Spend Billions to Revive Local News"-->{{cite Q|Q139594786}} * <!-- Joshua Benton (9 April 2019). "When local newspapers shrink, fewer people bother to run for mayor". Nieman Foundation for Journalism -->{{cite Q|Q63127216}} * <!--Stephen Bezruchka (2023) Inequality Kills Us All-->{{cite Q|Q136047815}} * <!--Stephen Bezruchka (2025) ''Born Sick in the USA''-->{{cite Q|Q138749292}} * <!--Renée DiResta (2024) Invisible Rulers: The People Who Turn Lies into Reality-->{{cite Q|Q135530439}} * <!--Robert Felix, Joshua A. Khavis, and Mikhail Pevzner (2024) "The effects of local newspaper closures on nonprofits’ executive compensation"-->{{cite Q|Q132730972}} * <!--Maxim Flößer (2024-03-06) "Keine Lokalzeitung -- mehr AfD", Kontext-->{{cite Q|Q125287792}} * <!--Pengjie Gao, Chang Lee, and Dermot Murphy (2018) "Financing Dies in Darkness? The Impact of Newspaper Closures on Public Finance"-->{{cite Q|Q55670016}} * <!--Spencer Graves (2024) "Wikipedia: The most democratic force on earth-->{{cite Q|Q137796922}} * <!--Spencer Graves and Bryan Bailey (2025) "We have to talk", blog at PeaceWorksKC.org-->{{cite Q|Q136126262}} * [[d:Q138038060|Dan Hind and Spencer Graves (2025) "Media Reform Coalition challenges anti-democratic media bias in the UK" on Wikiversity]]. * <!--Richard R. John (1995) Spreading the News: The American Postal System from Franklin to Morse-->{{cite Q|Q54641943}} * <!--Adam H. Johnson (2026-04-21) How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza-->{{cite Q|Q140073447}} * <!--Louis Johnston and Samuel H. Williamson, "What Was the U.S. GDP Then?" MeasuringWorth, 2026-->{{cite Q|Q56881105}} * <!-- Min Kim, Derrald Stice, Han Stice, and Roger M. White (2021) "Stop the presses! Or wait, we might need them: Firm responses to local newspaper closures and layoffs"-->{{cite Q|Q132459373}} * <!-- Robert W. McChesney; John Nichols (2010). The Death and Life of American Journalism (Bold Type Books) -->{{cite Q|Q104888067}}. * <!-- Robert W. McChesney; John Nichols (2021). "The Local Journalism Initiative: a proposal to protect and extend democracy". Columbia Journalism Review, 30 November 2021 -->{{cite Q|Q109978060}} * <!-- Robert W. McChesney; John Nichols (2022), To Protect and Extend Democracy, Recreate Local News Media (PDF), FreePress.net (updated 25 January 2022) -->{{cite Q|Q109978337|access-date=2024-06-23}} * <!--Alfred W. McCoy (2003-05-01) The politics of heroin : CIA complicity in the global drug trade : Afghanistan, Southeast Asia, Central America, Colombia-->{{cite Q|Q141317509}} * <!--Joel Mokyr (2017) A Culture of Growth: The Origins of the Modern Economy (Graz Schumpeter Lectures; Princeton University Press)-->{{cite Q|Q136118590}} * <!--Neff and Pickard (2024) "Funding Democracy: Public Media and Democratic Health in 33 Countries"-->{{cite Q|Q131468289}} * [[d:Q131398359|Victor Pickard (2020) ''Democracy without journalism? : confronting the misinformation society'' (Oxford U. Pr.)]]. * <!-- Victor Pickard (2023-05-12) "Another Media System is Possible: Ripping Open the Overton Window, from Platforms to Public Broadcasting"-->{{cite Q|Q131398460}} * <!--Doug Samuelson (2025) Assessing Israel’s Approach in Gaza-->{{cite Q|Q138843324}} * [[d:Q138037937|Dean Starkman and Spencer Graves (2025) "Dean Starkman and the watchdog that didn't bark anglais" on Wikiversity]]. * <!--Mira Sucharov (2022) Do American Jews Really Know What 'Zionist' Means?-->{{cite Q|Q125903777}} * [[d:Q134715465|Nikki Usher and Sanghoon Kim-Leffingwell (2022) "How Loud Does the Watchdog Bark? A Reconsideration of Local Journalism, News Non-profits, and Political Corruption", ''SSRN Electronic Journal'']]. * [[d:Q61013892|Horacio Verbitsky (1997) ''Un mundo sin periodistas'' (in Spanish: A world without journalists; Editorial Sudamericana)]]. [[Category:Communication]] [[Category:Political science]] [[Category:Law]] [[Category:Psychology]] [[Category:Sociology]] [[Category:Education]] [[Category:Economics]] [[Category:Media Literacy and You]] [[Category:Freedom and abundance]] <!-- https://en.wikiversity.org/wiki/Category_Review --> tao3hl3hrvm4it5jafqsdobxkjesa7h 2835374 2835373 2026-10-01T17:32:53Z DavidMCEddy 218607 typo 2835374 wikitext text/x-wiki [[File:Pharoah - James VI and I - Trump.png|thumb|Religious and media leaders from the time of the Pharaohs convinced common folk to give increasing shares of what they produced to elites.]] :''This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.'' == Invitation to edit this book == You, dear reader, are invited to contribute questions, ideas and citations to support or refute claims made in this book possibly adding chapters. Wikiversity like other Wikimedia Foundation Projects invites humans to [[w:Wikipedia:Be bold|“be bold but not reckless,”]] while writing from a [[Wikiversity:Disclosures|neutral point of view]], [[Wikiversity:Cite sources|citing credible sources]]. Others are invited to change or revert what you wrote. What stays tends to be written from a neutral point of view citing credible sources. If someone reverts your edit or you have a question, take it to the ''[[Wikiversity:FAQ|''''“Discuss”'''' page]]'' associated with the specific Wikiversity page most related to your concerns. Those who teach media literacy are encouraged to invite their students to debate and revise the contents of this book. Doing so would build on a tradition of [[:w:Wikipedia:Student assignments|instructors requiring students to edit wikipedia article(s).]] Editing [[:w:Wikipedia|Wikipedia]] and other [[:w:Wikimedia Foundation|Wikimedia Foundation]] projects like this book is itself an exercise in media literacy: :''Central tenets of media literacy might include writing from a neutral point of view citing credible sources and engaging others, some of whom may disagree, in civil, supportive conversations about what can and cannot be said based on a reasonable evaluation of the available evidence. Wikimedia rules invite contributors to do just that, encouraging them to “be bold but not reckless,” contributing revisions written from a neutral point of view, citing credible sources -- and raising other questions and concerns on the ''''“Discuss”'''' page associated with the specific Wikiversity page most related to your concerns, as mentioned above.''<ref>For more on this, see Graves (2024).</ref> == Text and self-help book and point of discuss == This book is intended both as a text and self-help book and as a point of discussion considering four levels of media literacy: :1. '''Think before you share''': Follow the money. Every media organization sells changes in audience behaviors to those who control much of their money. Major media everywhere promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to convince the public to give increasing shares of what they produce to elites to "protect them from designated evil others." To counter this, DiResta (2024, p. 335) recommends, "Think before you share." :2. '''Look for information to contradict preconceptions''' (Disconfirmation bias): [[w:Information is a public good: Designing experiments to improve government#Previous research|Virtually everyone]] (a) thinks they know more than they do ([[w:Overconfidence effect|overconfidence effect]]), and (b) prefers information and sources consistent with preconceptions ([[w:Confirmation bias|confirmation bias]]). The major media everywhere exploit this to please those who control most of the money for the media. Humans can counter this by searching for sources to help us understand our designated enemies. ''If we cannot explain circumstances under which we could see ourselves doing what we see our designated enemies doing, we have not looked hard enough.'' :3. '''Talk''': Push ourselves to have friendly supportive conversations with others with whom we may vehemently disagree, seeking common ground, agreeing to disagree agreeably where we differ, and building collaboration on areas of common concern.<ref>Graves and Bailey (2025).</ref> :4. '''Teach''': Humans who develop skills in the first three levels can leverage that knowledge in helping others acquire those skills. If each one teaches two<ref>"[[:w:Each one teach one|Each one teach one]]" is an African-American proverb from the time of legalized slavery. However, if each one teaches only one, the growth in literacy will only be linear. Having "each one teaching two", on average, unleashes the power of doubling and [[:w:exponential growth|exponential growth]], which has the potential of educating the entirety of humanity in a reasonable period of time -- namely after 33 doublings starting from one.</ref> in a certain period of time, that time period becomes a [[:w:Doubling time|doubling time]]. Ten doublings is a thousand -- actually 1,024 to be precise.<ref>2 time 2 = 4 times 2 = 8 times 2 = 16 times 2 = 32 times 2 = 64 times 2 = 128 times 2 = 256 times 2 = 512 times 2 = 1024: That's 10 doublings, as anyone with a modest understanding of modern digital [[:w:computer|computer]]s will tell you.</ref> Twenty doublings become a million. Thirty doublings become a billion. Three more doublings become 8 billion, the [[:w:World population|world population]] as of approximately 2022-11-15.<ref>This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.</ref> Many organizations, including several United Nations agencies and the [[Yonty Friesem on media education|Media Education Lab]], have been working on [[w:media literacy|media literacy]] for decades and have trained many.<ref>''[[Wikibooks:Antiracist Activism for Teachers and Students]]'' includes a chapter on [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools|Media Literacy In Schools]].</ref> This book is being written hoping to increase the effectiveness and accelerate the rate of growth in media literacy and thereby accelerate progress against many of the most pressing issues facing humanity today.<ref>[[w:Nolan Higdon|Nolan Higdon]] and Spencer Graves discussed marketing media literacy in a "[[:Category:Media reform to improve democracy|Media & Democracy]]" episode on, "[[Media literacy and why you should care]]".</ref> Much of this book is a [[w:Monograph|research monograph]] summarizing research that seems to have been underreported by the major media to avoid offending people who control most of the money for the media. These research results seem to be central to major political divisions. Each chapter ends in exercises to help the reader practice media literacy skills and have fun doing it. Remember: :''I am entitled to my [[Wiktionary:cockamamie|cockamamie]] ideas, and you are entitled to yours.'' Humor is important but must be offered in a way that does not offend others. If others are offended, they may be less interested in dialogue. The term "cockamamie" is used here, hoping that this style of [[w:Self-deprecation|self-deprecation]] might be more inviting for dialogue. ''Never say, "You're wrong." Instead, ask, "May I offer a contrary perspective?" Or "May I share with you another view that I've heard?"'' Much of the information in this book seems to have been largely overlooked and perhaps suppressed, apparently because it would either offend people who control substantial portions of the money for the media our would increase the cost of producing news; see the brief discussion of conflicts of interest by the major media in the next "Key claims" section. ==Key claims== * ''Primary drivers of every major conflict include differences between the media or difference in interpretation that the different parties find credible''. :-- This works, because everything we think we know is coded in systems of connections between neurons in our brains. These systems are more unique than fingerprints and evolve over time. The words we use do not mean the same to two different humans nor even to the same human at different points in time. In many cases these differences are inconsequential. ''Sometimes they are fatal.''<ref>Graves and Bailey (2026).</ref> :-- ''[[w:Social constructionism|Show me someone who knows the truth]], and I will show you someone who is dangerous'' -- especially during war or any other situation where humans may be moved to violence encouraged by their belief system.<ref>[[w:Collateral damage|Collateral damage]] that "they" commit proves to "us" that "they" are subhuman or at best criminally misled and must be resisted by any means necessary. By contrast, collateral damage that "we" commit is unfortunate but necessary.</ref> * ''The major media everywhere have [[w:Conflict of interest|conflicts of interest ]] in honestly reporting on [[v:Information is a public good per communications prof Pickard|anything that might offend anyone who controls large portions of the money for the media]].''<ref>Pickard and Graves (2025), accessed 2026-02-08; Pickard (2020).</ref> :--[[v:Media Reform Coalition challenges anti-democratic media bias in the UK|British journalist and media reform advocate Dan Hind]] said that the content produced by the [[w:BBC|BBC]] was frivolous, soap opera stuff, because leading media personalities know very little about issues of substance and believe "they might get in trouble if" they produced anything serious. Similar analyses seem to apply to the major media everywhere<ref>Hind and Graves (2025), accessed 2026-02-09.</ref> but may not apply to non-profit and local media, which seem more likely to produce [[w:Investigative journalism|investigative]] / [[v:Dean Starkman and the watchdog that didn't bark|accountability journalism]]:<ref>Usher and Kim-Leffingwell (2022); see also Starkman and Graves (2025), accessed 2026-02-09.</ref> [[w:Watchdog journalism|Watchdogs]] tend to protect the people who feed them. Argentine journalist [[w:Horacio Verbitsky|Horacio Verbitsky]] said, "Journalism is disseminating information that someone does not want known; the rest is [[w:propaganda|propaganda]]."<ref>p. 16 in Verbitsky (1997); English translation from [[Wikiquote:Horacio Verbitsky]], accessed 2026-02-09.</ref> * ''The major media everywhere create the stage upon which politicians read their lines.'' :-- Major media promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to make it easier for elites to pick everyone else's pockets. This is particularly effective with for-profit social media, which make money herding their audience into echo chambers, where erroneous preconceptions are reinforced, increasing political polarization and violence. [[Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen said]], "The shortest path to a click is anger or hate." A leading expert on for-profit social media is Renée DiResta,<ref>DiResta (2024).</ref> whose research documents how lies spread on social media threaten public health and prepped a small army of humans throughout the 2020 US presidential election cycle to believe that there were major deficiencies in the integrity of US election procedures. When Trump lost, he was able to recruit [[w:January 6 United States Capitol attack|a crowd to attack the capitol on January 6, 2021]]. Social media influencers made so much money spreading lies that it seemed profitable for them to file frivolous lawsuits ([[w:Strategic lawsuit against public participation|SLAPP]]), hoping that DiResta's legal bills would convince her to stop trying to expose their lies. After Republicans regained control of the US House in 2022, they subpoenaed her, claiming she had taken orders from the "[[w:Deep state|deep state]]" to tell Facebook to censor conservatives. [[Managing the good and the evils of social media|When interviewed for ''Media & Democracy'', she reported legal bills of $7 million]]. :-- The social psychology behind this phenomenon exploits especially [[w:confirmation bias|confirmation bias]]. It has contributed to [[Media Literacy and You/Media consolidation, social media, and political polarization|the dramatic increase in political polarization and violence worldwide]], especially since the end of the [[w:Fairness doctrine|Fairness doctrine]] in 1987. :-- Democracy may be best protected by local news nonprofits, managed jointly by journalists and boards selected at random from registered voters, according to Pickard (2023), discussed in the section below on "[[Media Literacy and You#Government subsidies for news|Government subsidies for news]]". :-- Their selection of acceptable topics for news and entertainment create and maintain the "[[w:Overton window|Overton window]]", which is the range of acceptable political discourse. For example, in early 1964, US President [[w:Lyndon B. Johnson|Lyndon Johnson]] understood that he could lose the 1964 presidential election that year if he were seen to be soft on communism. His response was to clandestinely provoke an attack on US naval vessels in the Gulf of Tonkin, which he could then denounce as "unprovoked". During a dark and stormy night 1964-08-04 the [[w:USS Maddox (DD-731)|USS ''Maddox'']] and [[w:USS Turner Joy|''Turner Joy'']] spent a couple of hours "defending themselves" against radar snow, then [[w:Gulf of Tonkin incident|reported that they had sunk two attacking North Vietnamese torpedo boats]]; subsequent investigations found no evidence of the reported attacks. That incident was used to justify the [[w:Gulf of Tonkin Resolution|Gulf of Tonkin Resolution]], with only two dissenting votes in the US Congress: Those two dissenters were defeated in their next reelection campaigns, illustrating the point that ::''the major media create the environment in which many politicians cannot get elected without betraying the nation.'' :-- Nick Hart,<ref name=Hart><!--Nick Hart-->{{cite Q|Q135663983}}</ref> President and CEO of the Data Foundation,<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> noted that President Trump in his first term signed the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] of 2019, which was bipartisan legislation ostensibly mandating evidence-informed public policy.<ref>Hart mentioned the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] when he was interviewed for [[Evidence-informed public policy|"Media & Democracy" 2025-07-31]].</ref> Tragically, the record since 2019 suggests that, ::''The US Congress is rarely allowed to consider solid research suppressed by the major media.'' * ''The development of technology is never neutral in its impact on inequality but is driven to benefit people with power.''<ref>Acemoglu and Johnson (2023)</ref>. :-- [[Media Literacy and You/The impact of the media on political economy since the time of the Pharaohs|Improvements in agricultural technology from pre-history to the time of King James of the King James bible were managed to benefit elites.]] Then pamphlets and newspapers began to appear, the head of state stopped granting as many monopolies, and commoners began getting permission to become entrepreneurs. That transformed economic stagnation into growth in GDP per capita adjusted for inflation, initiating the [[w:Industrial Revolution|Industrial Revolution]], as documented in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]]. It also led to increasing inequality until organized labor got enough political power to demand and get a bigger share of the fruits of their labors. :--[[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|In the US those benefits peaked during the Great Depression]], when the standard conservative mantra that blames the poor for their poverty did not sell newspapers. US President Franklin Roosevelt taxed the ultra-wealthy like they had never been taxed before or since, and dramatically reduced inequality, which continued to decline until increasing concentration of ownership of the media ushered in a new era of increasing inequality starting with the presidency of Ronald Reagan. :-- [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future#Role of the media|Acemoglu and Johnson insist that technology, including artificial intelligence, can be developed to benefit all. However, but it will not happen without action by the poor and middle class as follows]]: :# Alter the narrative, :# Build countervailing powers [like organized labor], and :# Develop technical, regulatory, and policy solutions to tackle specific aspects of technology’s social bias.<ref>Acemoglu and Johnson (2023, ch. 11).</ref> :-- For more on this, see, e.g., the chapter on [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|Fox, the Great Depression, the Great Recession, and our future]]. === The value of noncommercial news outlets === Some of the problems with the media and their contributions to increasing political polarization and violence are documented in the research summary on "[[Information is a public good: Designing experiments to improve government]]" and in the podcast series available on Wikiversity under "[[:Category:Media reform to improve democracy]]" with leading experts discussing their recommendations. One of the most compelling of the references discussed in that podcast series is Usher and Kim-Leffingwell (2022), who tallied all the federal prosecutions for political corruption in each of the 94 [[w:United States federal judicial district|US federal court district]]s between 2003 and 2019. During that period, the number of journalists in the US fell by a factor of roughly 3 -- between 60 and 70 percent. They found no statistically significant impact on federal prosecutions for political corruption of that decline in the number of journalists. However, each member of the [[w:Institute for Nonprofit News|Institute for Nonprofit News]] (INN) in a federal court district in one year was associated with on average 1.4 additional prosecutions for political corruption the following year. Since federal prosecutions for political corruption averaged roughly 10 per federal court district per year during that period, each member of INN in a federal court district one year was associated with a 14 percent increase in federal prosecutions the following year. This suggests that the major media outlets that had so dramatically reduced their staffs had not substantively reduced the amount of investigative journalism they did. If we assume that the people prosecuted for political corruption also control substantive advertising budgets, then the major media outlets have conflicts of interest in honestly reporting on such. They may report on it if some other organization like a member of INN does the research and they are threatened with a loss of audience from not reporting on it. :'''''Major point''''': You and I benefit, the vast majority of humans on earth benefit, from news reports presumably published by members of INN that contributed to those on average 1.4 additional prosecutions for political corruption estimated by Usher and Kim-Leffingwell (2022). We benefit even if we never heard about the news reports that contributed to those prosecutions. We benefit even if we have never heard of the news outlets that presumably did the investigative journalism behind those additional prosecutions. Why? Because on average those news reports likely deterred other incidents of political corruption, which likely contributed to broadly shared economic growth and the development of new technology that ultimately benefit the vast majority of humanity. Other aspects of this are documented in the research on the impact of [[w:news desert|news desert]]s, which we summarize next. === Costs increase in news deserts=== There's a growing body of research describing what happens when local newspapers die. Perhaps most important, a 2018 research report by Gao et al. reported that the death of a local newspaper was followed by … increases in local tax revenue, averaging $85 per human per year.<ref name = Gao2018>Gao et al. (2018).</ref> That $85 was roughly 13 hundredths of a percent of the 2019 US GDP. That's mentioned in the 2025-07-17 interview with [[Democratic delusions: Fix the media to fix democracy|Natalie Fenton about her new book, ''Democratic Delusions, How the Media Hollows out democracy and What We Can Do About It'']]. One of the most spectacular example of the cost of a news desert is the [[w:City of Bell scandal|Scandal of Bell, California]]. Their local newspaper died around 1999. Roughly a decade later the city was nearly bankrupt in spite of having property tax rates among the highest in the nation. An investigation by the ''[[w:Los Angeles Times|Los Angeles Times]]'' documented that the city manager had a compensation package worth $1.5 million a year, well over double that of the President of the United States. Other senior city officials were similarly well-remunerated. Some of the city officials went to jail over that. Did the city manager decide after 1999, "Wow: The watchdog is dead. Let's have a party"? Malfeasance also increases in business as pollution and workplace accidents increase as does the cost of capital, because investors know their money is not as secure without a local newspaper. That leads to a reduction in investments in new products, services and processes -- slowing economic growth. See "[[Local newspapers limit malfeasance]]", esp. Kim et al. (2021). And executive compensation in increases in nonprofits, so less of what people donate goes to the charitable purpose for which they donated, according to Felix et al. (2024). Also, voter participation and split-ticket voting decline, per Benton (2019) and other references discussed in "[[Information is a public good: Designing experiments to improve government]]". And the ultra-right does better, as noted in [[News from Germany 1900-1945 and implications for today]] and the section on "[[Information is a public good: Designing experiments to improve government#Previous research|Previous research]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]".<ref>Flößer (2024).</ref> The 0.13 percent of GDP savings estimated by Gao et al. (2018) is roughly $120 per human per year. With over 300 million humans in the U.S, that is roughly $40 billion nationwide. {| class="wikitable" |+ Table 1. Costs increase in news deserts |- ! Entity !! What !!Source |- | local government || costs incr. 0.13% of GDP || Gao et al. (2018) |- | local businesses || pollution & workplace accidents incr., innovation & econ growth decr. || Kim et al. (2021) |- | nonprofits || exec. compensation incr. || Felix et al. (2024) |- | rowspan=2 | elections | voter participation & split-ticket voting decl. || Benton (2019) |- | Ultra-right does better || Flößer (2024) |} === Government subsidies for news === John (1995) documented how in the first half of the nineteenth century the US had more independent newspaper publishers per million population than at any other time or place in human history.<ref>This is discussed in the 2025-06-08 [[Media concentration per Columbia History Professor Richard John|interview with him]], available on Wikiversity under [[:Category:Media reform to improve democracy]], accessed 2026-04-30.</ref> This encouraged literacy and limited political corruption, both of which helped [[The Great American Paradox|the early United States stay together and grow]] while contemporary [[w:New Spain|New Spain]] / [[w:Mexico|Mexico]], fractured, shrank, and stagnated economically. As documented with Figure 1 in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]], that growth catapulted the young United States into its current position of dominance in the international political economy, a position it has been losing since at least 1990 -- or since the Reagan Revolution began in 1981, according to the analysis in the chapter below on [[/Fox, the Great Depression, the Great Recession, and our future/]]. Other countries now have stronger democracies due in part to government subsidies for media in the range of 0.05 and 0.25 percent of GDP with a firewall that limits political interference in the content, according to Neff and Pickard (2024). Table 1 in "[[Information is a public good: Designing experiments to improve government]] compares media subsidies in various places with "other points of reference". McChesney and Nichols (2010, pp. 310-311, note 88) suggested that the relatively high rate of economic growth of the economy in the early US was due in part to postal subsidies under the US [[w:Postal Service Act|Postal Service Act]] of 1792.<ref>See also the Wikiversity article on "[[The Great American Paradox]]", accessed 2026-04-30.</ref> They estimated those subsidies at 0.21 percent of GDP. To improve the current political economy of the US, they recommended subsidies of 0.15 percent of GDP distributed to local news nonprofits on the basis of local elections.<ref>McChesney and Nichols (2021, 2022).</ref> The Wikipedia article on "[[Information is a public good: Designing experiments to improve government]]" documents how some jurisdictions can devote that much money to local news nonprofits by matching what they spend on accounting, advertising, and public relations.<ref>See the section on "[[Information is a public good: Designing experiments to improve government#Sampling units / experimental polities|Sampling units / experimental polities]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]", accessed 2026-04-30.</ref> Pickard (2023) describes three basic strategies for confronting concentrated commercial media power: (1) break them up, (2) regulate them, and (3) create non-commercial, public alternatives. A fourth possibility might be [[w:externality|a graduated tax on income and wealth]] in proportion to the threat that major corporations pose to democracy. One class of noncommercial alternatives that Pickard mentions is local multimedia / Public Media Centers (PMCs) with management split between local journalists and boards, e.g., selected at random from registered voters. A key here is to have the boards selected in a way that cannot be influenced by people with power, whether business or political elites. Picard recommends considering '''six discrete layers''' when discussing PMCs, each of which, he says, must be radically democratised: # funding, # governance, # ascertainment (to determine a community’s ''critical information needs''), # infrastructure (including universal broadband service), # algorithmic (e.g., not allowing companies like Google and Facebook to suppress indexing information the might challenge their hegemony of those markets, [[w:Deep web|treating them like pedophilia and the Islamic State]]), # engagement, involving local communities in making their own news and in communicating their own stories; this is paramount to building trust and the grassroots-level support that this new local journalistic model requires. All this needs to be managed in ways that provide substantive support to news deserts and underserved communities that have long been subjected to various kinds of informational redlining. This might be done by including the proposed PMCs within local libraries staffed by professional journalists, who provide training in media literacy in local schools for children and supervise students producing school newspapers. PMCs could host regular, e.g., monthly events, where local residents could share their concerns with journalist, who would use that input to help prioritize different issues for news coverage. Journalist could also coach local residents in how to research issues and collaborate with journalists in producing news reports that may be better researched and more relevant to local concerns than could be produced without such collaboration. Management of such PMCs might be split between journalists on staff and boards of, e.g., six members selected at random from voter registration rolls serving staggered terms of one year with a new member rotated in every 2 months. Another alternative that could be done in parallel with local PMCs calls for 200 journalists in each US Congressional district funded at $10 billion annually in 2022 dollars, which is just a little under 4 hundredths of one percent of GDP; if such allocations are expressed as fractions of a percent of GDP, they would grow naturally with the economy. (The nominal GDP for the US was roughly $26.1 trillion in 2022.<ref>Johnston and Williamson (2026).</ref> For 2026 it is estimated at $32.4 trillion.<ref>[[w:United States|United States]], accessed 2026-04-30.</ref>) A similar model is the [[w:BBC|BBC]]’s Local Democracy Reporting Service (LDRS), in which the BBC funds journalists to cover the work of local councils and other local public bodies, funded at £8 million per year, which is a little under 2 hundredths of a percent of the [[w:United Kingdom|UK]]'s GDP of £7.27 trillion.<ref>[[w:United Kingdom|United Kingdom]], accessed 2026-04-30.</ref> Pickard (2023) ended by saying, "Today we face a crossroads: technocracy and oligarchy from above or radical democracy and structural reform from below. ... [T]his is not just a journalism crisis: it is a democracy crisis." ==Table of Contents== *[[/Introduction/]] including an exercise, asking all to discuss perceptions of the settlement of ''[[w:Dominion Voting Systems v. Fox News Network|Dominion Voting Systems v. Fox News Network]]'' in a friendly supportive manner with humans with whom they may vehemently disagree, because the alternative could be killing humans over misunderstandings. ===Part I. The media and political economy=== # [[/The impact of the media on political economy since the time of the Pharaohs/]] describes how religious leaders in hierarchical societies prior to [[w:James VI and I|King James of the King James bible]] convinced commoners to live in poverty while giving increasing shares of what they produced so religious and secular elites could live in opulence. During the reign of King James, pamphlets and newspapers began to compete with the church for helping commoners understand their roles in society. This produced the Industrial Revolution and modern democracies. Media consolidation since World War II slowed, then reversed this trend. # [[/Fox, the Great Depression, the Great Recession, and our future/]] describes the unprecedented performance of the US political economy during the presidency of Franklin Roosevelt (FDR), insisting that much of what FDR achieved can be replicated, giving a media system that supports honest discussion of the available evidence. # [[/Media consolidation, social media, and political polarization/]] (Combine from McChesney and Nichols discussing the [[w:Postal Service Act|US Postal Service Act]] of 1792 with [[Media concentration per Columbia History Professor Richard John]], the section on "[[v:Information is a public good: Designing experiments to improve government#Threats from social media|Threats from social media]]" in "[[Information is a public good: Designing experiments to improve government]], and the comments by [[v:Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen that, "the shortest path to a click is anger or hate."]]. ===Part II. The media and war=== # [[/Deterrence without threat/]]: The historical record is clear: Nations that have prepared for war often got war, not peace. This happens for at least two reasons: First, some leaders cannot resist the temptation to use force inappropriately, sometimes clandestinely provoking others to do things that are then denounced as "unprovoked"; sometimes the media environment pushes them to do such. Alternatively, potential adversaries may believe -- or claim -- that you are actually preparing a first strike, and they must move preemptively or lose their ability to retaliate adequately. We can avoid these possibilities with three supportive policies: [a] Legislation that ''prohibits'' projecting force beyond our own borders. [b] Civilian-based defense training in nonviolent noncooperation like what helped Denmark survive Nazi occupation with minimal damage. And [c] a media system that penalizes rather than encourages a bellicose foreign policy. # [[/Responding to a nuclear attack/]]: The ''worst'' response to a nuclear attack would be a nuclear response: The death toll from the 1945 [[w:Atomic bombings of Hiroshima and Nagasaki|Atomic bombings of Hiroshima and Nagasaki]] was estimated at between 150,000 and a quarter of a million. By contrast, simulations of nuclear wars of different magnitudes estimated that between 4 and 95 percent of humanity around the world would starve to death if they did not die of something else sooner. The range depends on whether the war was "limited", e.g., between India and Pakistan, and massive between the US and Russia. (Also add material from [[Nuclear weapons and effective defense]]). # [[/Threats from excessive government secrecy/]] (draft in [https://sanjosepeace.org/restrict-secrecy-more-than-data-collection/ "Restrict secrecy more than data collection"], adding material from [https://kkfi.org/program-episodes/does-us-government-secrecy-threaten-national-security/ Connelly (2023) ''The Declassification Engine: What History Reveals About America's Top Secrets''], [[Wikipedia:Moynihan Commission on Government Secrecy]] and [[1998 Embassy bombings and September 11]]. # [[/Shouting fire in a crowded theater/|Shouting ''fire'' in a crowded theater]]: Legal concerns about "[[w:Shouting fire in a crowded theater|Shouting ''fire'' in a crowded theater]]" date, at least in large part, from the [[w:Supreme Court of the United States|US Supreme Court]] decisions in ''[[w:Schenck v. United States|Schenck v. United States]]'' (1919) and ''[[w: Brandenburg v. Ohio| Brandenburg v. Ohio]]'' (1969). In ''Schenck'' the Court ruled that the government had a right to imprison Schenck and others, because their distribution of fliers encouraging draft resistance presented a [[w:clear and present danger|clear and present danger]] to the efficacy of ongoing military activities during [[w:World War I|World War I]], then in progress. The Court in ''Brandenburg'' held that the government cannot punish inflammatory speech ''unless that speech is "directed to inciting or producing imminent lawless action and is likely to incite or produce such action".'' Some could argue that many uses of military force by the US and Israel since 1948 have violated international law, encouraged by biases in the major US media "directed to inciting or producing imminent lawless action", though it may not be feasible to convince a court of that. Still, it might be useful to simulate such a case in a mock trial like the 1966 [[w:Russell Tribunal|Russell Tribunal]].<ref>Andersen (2006) provides such documentation for several such uses of force. Andersen (2026) and Johnson (2026) organize evidence supporting such claims for the current [[w:Gaza war|Gaza war]], which began with [[w:October 7 attacks|Palestinian attacks 2023-10-07]]. Might, e.g., Palestinians -- or at least Palestinian Americans -- be able to sue the [[w:Anti-Defamation League|Anti-Defamation League]] (ADL), the [[w:AIPAC|American Israel Public Affairs Committee]] (AIPAC), and all the major media outlets in the US for inciting genocide in the current [[w:Gaza war|Gaza war]]? That history includes routine suppression of coverage by the major media especially in the US of routine denial of equal protection of Israeli laws to non-Jews in Israel and under Israeli occupation, including suppression of Israeli violence against nonviolent protestors peaceably assembling and petitioning for a redress of grievances combined with over reporting of Palestinian violence and unquestioning coverage of fraudulent claims of Palestinian violence by Israel and supporters. The suppressions included underreporting of Palestinian nonviolence such as the [[w:2018–2019 Gaza border protests|(2018-2019) Great March of Return]], and suppression of the grievances inspiring such nonviolence such as indefinite detention without charges of thousands of Palestinians, including children, routine destruction of Palestinian property by settlers, confiscation of Palestinian property at gunpoint, closing [[w:Gaza Strip|Gaza]] to international trade, and maintaining Gaza on starvation rations. These routine biases in reporting have been encouraged by charges that more honest reporting would be "[[w:Antisemitism|antisemetic]], according to the ADL and AIPAC. This denial of coverage thereby encouraged Israel to increase the rate of such violations until the [[w:October 7 attacks|2023-10-07 attacks on Israel from Gaza]] unleashed Israeli "retaliations" way out of proportion to the alleged provocation. Sucharov (2022) reported that 69% of American Jews opposed privileging Jews over non-Jews in Israel. Their support of Israel in the current Gaza war is consistent with the media biases documented by Johnson (2026) and others including Andersen (2006, 2026). Regarding whether Israel could achieve anything positive from this war, Samuelson (2025) is skeptical. He summarized quantitative analyses of 60 previous insurgencies. The results including the observation that it is exceedingly difficult to defeat an insurgency without responding to the grievances that support it without force ratios far beyond Israel's resources.</ref> ===Part III. Climate, immigrants, education, public health, and criminal justice=== # [[/Global warming/]] [Summarize research especially on conflicts of interest of major media in honestly reporting on this issue and the research on global warming itself and activities of groups concerned about this issue. Decompose into global population times CO2 equivalents per human.] # [[/Immigrants/]] [Summarize research documenting that [[w:Sanctuary city|sanctuary cities tend to have higher median incomes and no more crime than non-sanctuary jurisdictions]], and some studies report less crime. Moreover economists have documented that immigrants tend to be more entrepreneurial, overrepresented in patent applications, and generally increasing the rate of economic growth. See, e.g., Aghion et al. (2022) ''The power of creative destruction''; Aghion shared the 2025 Nobel Memorial Prize in Economics with two others.] # [[/Education/]] (draft in [[Invest in children]].) # [[/Public health/]] [Draft in [[UN public health data]] to be revised to be consistent with Bezruchka (2023, 2025).] # [[/Substance abuse and addictive behavior/]] (Research cited in "[[Wikipedia:War on drugs]]" insists that the US and the world would have fewer problems with substance abuse and addiction problems with 100 percent public funding for treatment programs and complete decriminalization of possession and use of retail quantities of addictive substances. We would also likely have fewer problems with immigrants, as that would make it harder for the US to intervene in the internal affairs of foreign countries funded off the books, as exposed in the [[w:Iran–Contra affair|Iran–Contra affair]]. See [[w:Alfred W. McCoy|Alfred W. McCoy]] (1972; 3rd ed. 2003) ''The politics of heroin''. Journalist [[w:Gary Webb|Gary Webb]] published similar claims that the US intervention in Nicaragua in the Iran-Contra Affair was funded in part by drug money. The story was officially retracted by the ''San José Mercury News'', and Webb allegedly killed himself with 2 bullets to the head. # [[/Criminal justice/]] (The section on "[[w:United States incarceration rate#Editorial policies of major media|Editorial policies of major media]]" in "[[Wikipedia:United States incarceration rate]]" cites research claiming that within the range range of experience in the US political economy since 1925, the incarceration rate is uncorrelated with crime: It's a function of the public's perception of crime, and that's a function of the media. That suggest that the US would be safer and more prosperous if incarceration policies were driving more by research than by editorial policies of the media. For example, there is also research that says that incarcerees who receive visits are less likely to recidivate, but that evidence is overlooked when convicts are incarcerated substantial distance from their family and friends and when the cost of phone services is substantially higher for incarcerees than among the general pubic. Also, it's known that better educated incarcerees are less likely to recidivate, but it's difficult and maybe impossible for many incarcerees to obtain education in prison.) # [[/Empower women and girls/]] [Cite research claiming that a primary restraint on population growth is empowering women and girls. Empowering women and girls is not just a matter of equity: It is also a means to reduce the threats of global warming, of increasing exposure to animal diseases and other problems that come with unrestrained population growth.] === Continuation === * [[/The evolving media literacy movement/]] to invite others to keep this book current with the evolving understanding of media literacy, how to encourage and promote it and the benefits of doing so. ==See also== * [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools]] ==Notes== {{reflist}} ==Bibliography== * <!--Daron Acemoğlu and Simon Johnson (2023) Power and Progress-->{{cite Q|Q125292212}} * <!--Robin Andersen (2006) A century of media, a century of war-->{{cite Q|Q138795568}} * <!--Robin Andersen (2026-06-02) The Complicit Lens: US Media Coverage of Israel’s Genocide in Gaza-->{{cite Q|Q138796307}} * <!--Perry Bacon Jr. (2022-10-17) "America Should Spend Billions to Revive Local News"-->{{cite Q|Q139594786}} * <!-- Joshua Benton (9 April 2019). "When local newspapers shrink, fewer people bother to run for mayor". Nieman Foundation for Journalism -->{{cite Q|Q63127216}} * <!--Stephen Bezruchka (2023) Inequality Kills Us All-->{{cite Q|Q136047815}} * <!--Stephen Bezruchka (2025) ''Born Sick in the USA''-->{{cite Q|Q138749292}} * <!--Renée DiResta (2024) Invisible Rulers: The People Who Turn Lies into Reality-->{{cite Q|Q135530439}} * <!--Robert Felix, Joshua A. Khavis, and Mikhail Pevzner (2024) "The effects of local newspaper closures on nonprofits’ executive compensation"-->{{cite Q|Q132730972}} * <!--Maxim Flößer (2024-03-06) "Keine Lokalzeitung -- mehr AfD", Kontext-->{{cite Q|Q125287792}} * <!--Pengjie Gao, Chang Lee, and Dermot Murphy (2018) "Financing Dies in Darkness? The Impact of Newspaper Closures on Public Finance"-->{{cite Q|Q55670016}} * <!--Spencer Graves (2024) "Wikipedia: The most democratic force on earth-->{{cite Q|Q137796922}} * <!--Spencer Graves and Bryan Bailey (2025) "We have to talk", blog at PeaceWorksKC.org-->{{cite Q|Q136126262}} * [[d:Q138038060|Dan Hind and Spencer Graves (2025) "Media Reform Coalition challenges anti-democratic media bias in the UK" on Wikiversity]]. * <!--Richard R. John (1995) Spreading the News: The American Postal System from Franklin to Morse-->{{cite Q|Q54641943}} * <!--Adam H. Johnson (2026-04-21) How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza-->{{cite Q|Q140073447}} * <!--Louis Johnston and Samuel H. Williamson, "What Was the U.S. GDP Then?" MeasuringWorth, 2026-->{{cite Q|Q56881105}} * <!-- Min Kim, Derrald Stice, Han Stice, and Roger M. White (2021) "Stop the presses! Or wait, we might need them: Firm responses to local newspaper closures and layoffs"-->{{cite Q|Q132459373}} * <!-- Robert W. McChesney; John Nichols (2010). The Death and Life of American Journalism (Bold Type Books) -->{{cite Q|Q104888067}}. * <!-- Robert W. McChesney; John Nichols (2021). "The Local Journalism Initiative: a proposal to protect and extend democracy". Columbia Journalism Review, 30 November 2021 -->{{cite Q|Q109978060}} * <!-- Robert W. McChesney; John Nichols (2022), To Protect and Extend Democracy, Recreate Local News Media (PDF), FreePress.net (updated 25 January 2022) -->{{cite Q|Q109978337|access-date=2024-06-23}} * <!--Alfred W. McCoy (2003-05-01) The politics of heroin : CIA complicity in the global drug trade : Afghanistan, Southeast Asia, Central America, Colombia-->{{cite Q|Q141317509}} * <!--Joel Mokyr (2017) A Culture of Growth: The Origins of the Modern Economy (Graz Schumpeter Lectures; Princeton University Press)-->{{cite Q|Q136118590}} * <!--Neff and Pickard (2024) "Funding Democracy: Public Media and Democratic Health in 33 Countries"-->{{cite Q|Q131468289}} * [[d:Q131398359|Victor Pickard (2020) ''Democracy without journalism? : confronting the misinformation society'' (Oxford U. Pr.)]]. * <!-- Victor Pickard (2023-05-12) "Another Media System is Possible: Ripping Open the Overton Window, from Platforms to Public Broadcasting"-->{{cite Q|Q131398460}} * <!--Doug Samuelson (2025) Assessing Israel’s Approach in Gaza-->{{cite Q|Q138843324}} * [[d:Q138037937|Dean Starkman and Spencer Graves (2025) "Dean Starkman and the watchdog that didn't bark anglais" on Wikiversity]]. * <!--Mira Sucharov (2022) Do American Jews Really Know What 'Zionist' Means?-->{{cite Q|Q125903777}} * [[d:Q134715465|Nikki Usher and Sanghoon Kim-Leffingwell (2022) "How Loud Does the Watchdog Bark? A Reconsideration of Local Journalism, News Non-profits, and Political Corruption", ''SSRN Electronic Journal'']]. * [[d:Q61013892|Horacio Verbitsky (1997) ''Un mundo sin periodistas'' (in Spanish: A world without journalists; Editorial Sudamericana)]]. [[Category:Communication]] [[Category:Political science]] [[Category:Law]] [[Category:Psychology]] [[Category:Sociology]] [[Category:Education]] [[Category:Economics]] [[Category:Media Literacy and You]] [[Category:Freedom and abundance]] <!-- https://en.wikiversity.org/wiki/Category_Review --> b1o36xdkmo4f76roxmqi8p82a3zq51h 2835401 2835374 2026-10-01T22:54:19Z DavidMCEddy 218607 add Baker and Murphy 2026 2835401 wikitext text/x-wiki [[File:Pharoah - James VI and I - Trump.png|thumb|Religious and media leaders from the time of the Pharaohs convinced common folk to give increasing shares of what they produced to elites.]] :''This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.'' == Invitation to edit this book == You, dear reader, are invited to contribute questions, ideas and citations to support or refute claims made in this book possibly adding chapters. Wikiversity like other Wikimedia Foundation Projects invites humans to [[w:Wikipedia:Be bold|“be bold but not reckless,”]] while writing from a [[Wikiversity:Disclosures|neutral point of view]], [[Wikiversity:Cite sources|citing credible sources]]. Others are invited to change or revert what you wrote. What stays tends to be written from a neutral point of view citing credible sources. If someone reverts your edit or you have a question, take it to the ''[[Wikiversity:FAQ|''''“Discuss”'''' page]]'' associated with the specific Wikiversity page most related to your concerns. Those who teach media literacy are encouraged to invite their students to debate and revise the contents of this book. Doing so would build on a tradition of [[:w:Wikipedia:Student assignments|instructors requiring students to edit wikipedia article(s).]] Editing [[:w:Wikipedia|Wikipedia]] and other [[:w:Wikimedia Foundation|Wikimedia Foundation]] projects like this book is itself an exercise in media literacy: :''Central tenets of media literacy might include writing from a neutral point of view citing credible sources and engaging others, some of whom may disagree, in civil, supportive conversations about what can and cannot be said based on a reasonable evaluation of the available evidence. Wikimedia rules invite contributors to do just that, encouraging them to “be bold but not reckless,” contributing revisions written from a neutral point of view, citing credible sources -- and raising other questions and concerns on the ''''“Discuss”'''' page associated with the specific Wikiversity page most related to your concerns, as mentioned above.''<ref>For more on this, see Graves (2024).</ref> == Text and self-help book and point of discuss == This book is intended both as a text and self-help book and as a point of discussion considering four levels of media literacy: :1. '''Think before you share''': Follow the money. Every media organization sells changes in audience behaviors to those who control much of their money. Major media everywhere promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to convince the public to give increasing shares of what they produce to elites to "protect them from designated evil others." To counter this, DiResta (2024, p. 335) recommends, "Think before you share." :2. '''Look for information to contradict preconceptions''' (Disconfirmation bias): [[w:Information is a public good: Designing experiments to improve government#Previous research|Virtually everyone]] (a) thinks they know more than they do ([[w:Overconfidence effect|overconfidence effect]]), and (b) prefers information and sources consistent with preconceptions ([[w:Confirmation bias|confirmation bias]]). The major media everywhere exploit this to please those who control most of the money for the media. Humans can counter this by searching for sources to help us understand our designated enemies. ''If we cannot explain circumstances under which we could see ourselves doing what we see our designated enemies doing, we have not looked hard enough.'' :3. '''Talk''': Push ourselves to have friendly supportive conversations with others with whom we may vehemently disagree, seeking common ground, agreeing to disagree agreeably where we differ, and building collaboration on areas of common concern.<ref>Graves and Bailey (2025).</ref> :4. '''Teach''': Humans who develop skills in the first three levels can leverage that knowledge in helping others acquire those skills. If each one teaches two<ref>"[[:w:Each one teach one|Each one teach one]]" is an African-American proverb from the time of legalized slavery. However, if each one teaches only one, the growth in literacy will only be linear. Having "each one teaching two", on average, unleashes the power of doubling and [[:w:exponential growth|exponential growth]], which has the potential of educating the entirety of humanity in a reasonable period of time -- namely after 33 doublings starting from one.</ref> in a certain period of time, that time period becomes a [[:w:Doubling time|doubling time]]. Ten doublings is a thousand -- actually 1,024 to be precise.<ref>2 time 2 = 4 times 2 = 8 times 2 = 16 times 2 = 32 times 2 = 64 times 2 = 128 times 2 = 256 times 2 = 512 times 2 = 1024: That's 10 doublings, as anyone with a modest understanding of modern digital [[:w:computer|computer]]s will tell you.</ref> Twenty doublings become a million. Thirty doublings become a billion. Three more doublings become 8 billion, the [[:w:World population|world population]] as of approximately 2022-11-15.<ref>This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.</ref> Many organizations, including several United Nations agencies and the [[Yonty Friesem on media education|Media Education Lab]], have been working on [[w:media literacy|media literacy]] for decades and have trained many.<ref>''[[Wikibooks:Antiracist Activism for Teachers and Students]]'' includes a chapter on [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools|Media Literacy In Schools]].</ref> This book is being written hoping to increase the effectiveness and accelerate the rate of growth in media literacy and thereby accelerate progress against many of the most pressing issues facing humanity today.<ref>[[w:Nolan Higdon|Nolan Higdon]] and Spencer Graves discussed marketing media literacy in a "[[:Category:Media reform to improve democracy|Media & Democracy]]" episode on, "[[Media literacy and why you should care]]".</ref> Much of this book is a [[w:Monograph|research monograph]] summarizing research that seems to have been underreported by the major media to avoid offending people who control most of the money for the media. These research results seem to be central to major political divisions. Each chapter ends in exercises to help the reader practice media literacy skills and have fun doing it. Remember: :''I am entitled to my [[Wiktionary:cockamamie|cockamamie]] ideas, and you are entitled to yours.'' Humor is important but must be offered in a way that does not offend others. If others are offended, they may be less interested in dialogue. The term "cockamamie" is used here, hoping that this style of [[w:Self-deprecation|self-deprecation]] might be more inviting for dialogue. ''Never say, "You're wrong." Instead, ask, "May I offer a contrary perspective?" Or "May I share with you another view that I've heard?"'' Much of the information in this book seems to have been largely overlooked and perhaps suppressed, apparently because it would either offend people who control substantial portions of the money for the media our would increase the cost of producing news; see the brief discussion of conflicts of interest by the major media in the next "Key claims" section. ==Key claims== * ''Primary drivers of every major conflict include differences between the media or difference in interpretation that the different parties find credible''. :-- This works, because everything we think we know is coded in systems of connections between neurons in our brains. These systems are more unique than fingerprints and evolve over time. The words we use do not mean the same to two different humans nor even to the same human at different points in time. In many cases these differences are inconsequential. ''Sometimes they are fatal.''<ref>Graves and Bailey (2026).</ref> :-- ''[[w:Social constructionism|Show me someone who knows the truth]], and I will show you someone who is dangerous'' -- especially during war or any other situation where humans may be moved to violence encouraged by their belief system.<ref>[[w:Collateral damage|Collateral damage]] that "they" commit proves to "us" that "they" are subhuman or at best criminally misled and must be resisted by any means necessary. By contrast, collateral damage that "we" commit is unfortunate but necessary.</ref> * ''The major media everywhere have [[w:Conflict of interest|conflicts of interest ]] in honestly reporting on [[v:Information is a public good per communications prof Pickard|anything that might offend anyone who controls large portions of the money for the media]].''<ref>Pickard and Graves (2025), accessed 2026-02-08; Pickard (2020).</ref> :--[[v:Media Reform Coalition challenges anti-democratic media bias in the UK|British journalist and media reform advocate Dan Hind]] said that the content produced by the [[w:BBC|BBC]] was frivolous, soap opera stuff, because leading media personalities know very little about issues of substance and believe "they might get in trouble if" they produced anything serious. Similar analyses seem to apply to the major media everywhere<ref>Hind and Graves (2025), accessed 2026-02-09.</ref> but may not apply to non-profit and local media, which seem more likely to produce [[w:Investigative journalism|investigative]] / [[v:Dean Starkman and the watchdog that didn't bark|accountability journalism]]:<ref>Usher and Kim-Leffingwell (2022); see also Starkman and Graves (2025), accessed 2026-02-09.</ref> [[w:Watchdog journalism|Watchdogs]] tend to protect the people who feed them. Argentine journalist [[w:Horacio Verbitsky|Horacio Verbitsky]] said, "Journalism is disseminating information that someone does not want known; the rest is [[w:propaganda|propaganda]]."<ref>p. 16 in Verbitsky (1997); English translation from [[Wikiquote:Horacio Verbitsky]], accessed 2026-02-09.</ref> * ''The major media everywhere create the stage upon which politicians read their lines.'' :-- Major media promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to make it easier for elites to pick everyone else's pockets. This is particularly effective with for-profit social media, which make money herding their audience into echo chambers, where erroneous preconceptions are reinforced, increasing political polarization and violence. [[Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen said]], "The shortest path to a click is anger or hate." A leading expert on for-profit social media is Renée DiResta,<ref>DiResta (2024).</ref> whose research documents how lies spread on social media threaten public health and prepped a small army of humans throughout the 2020 US presidential election cycle to believe that there were major deficiencies in the integrity of US election procedures. When Trump lost, he was able to recruit [[w:January 6 United States Capitol attack|a crowd to attack the capitol on January 6, 2021]]. Social media influencers made so much money spreading lies that it seemed profitable for them to file frivolous lawsuits ([[w:Strategic lawsuit against public participation|SLAPP]]), hoping that DiResta's legal bills would convince her to stop trying to expose their lies. After Republicans regained control of the US House in 2022, they subpoenaed her, claiming she had taken orders from the "[[w:Deep state|deep state]]" to tell Facebook to censor conservatives. [[Managing the good and the evils of social media|When interviewed for ''Media & Democracy'', she reported legal bills of $7 million]]. :-- The social psychology behind this phenomenon exploits especially [[w:confirmation bias|confirmation bias]]. It has contributed to [[Media Literacy and You/Media consolidation, social media, and political polarization|the dramatic increase in political polarization and violence worldwide]], especially since the end of the [[w:Fairness doctrine|Fairness doctrine]] in 1987. :-- Democracy may be best protected by local news nonprofits, managed jointly by journalists and boards selected at random from registered voters, according to Pickard (2023), discussed in the section below on "[[Media Literacy and You#Government subsidies for news|Government subsidies for news]]". :-- Their selection of acceptable topics for news and entertainment create and maintain the "[[w:Overton window|Overton window]]", which is the range of acceptable political discourse. For example, in early 1964, US President [[w:Lyndon B. Johnson|Lyndon Johnson]] understood that he could lose the 1964 presidential election that year if he were seen to be soft on communism. His response was to clandestinely provoke an attack on US naval vessels in the Gulf of Tonkin, which he could then denounce as "unprovoked". During a dark and stormy night 1964-08-04 the [[w:USS Maddox (DD-731)|USS ''Maddox'']] and [[w:USS Turner Joy|''Turner Joy'']] spent a couple of hours "defending themselves" against radar snow, then [[w:Gulf of Tonkin incident|reported that they had sunk two attacking North Vietnamese torpedo boats]]; subsequent investigations found no evidence of the reported attacks. That incident was used to justify the [[w:Gulf of Tonkin Resolution|Gulf of Tonkin Resolution]], with only two dissenting votes in the US Congress: Those two dissenters were defeated in their next reelection campaigns, illustrating the point that ::''the major media create the environment in which many politicians cannot get elected without betraying the nation.'' :-- Nick Hart,<ref name=Hart><!--Nick Hart-->{{cite Q|Q135663983}}</ref> President and CEO of the Data Foundation,<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> noted that President Trump in his first term signed the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] of 2019, which was bipartisan legislation ostensibly mandating evidence-informed public policy.<ref>Hart mentioned the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] when he was interviewed for [[Evidence-informed public policy|"Media & Democracy" 2025-07-31]].</ref> Tragically, the record since 2019 suggests that, ::''The US Congress is rarely allowed to consider solid research suppressed by the major media.'' * ''The development of technology is never neutral in its impact on inequality but is driven to benefit people with power.''<ref>Acemoglu and Johnson (2023)</ref>. :-- [[Media Literacy and You/The impact of the media on political economy since the time of the Pharaohs|Improvements in agricultural technology from pre-history to the time of King James of the King James bible were managed to benefit elites.]] Then pamphlets and newspapers began to appear, the head of state stopped granting as many monopolies, and commoners began getting permission to become entrepreneurs. That transformed economic stagnation into growth in GDP per capita adjusted for inflation, initiating the [[w:Industrial Revolution|Industrial Revolution]], as documented in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]]. It also led to increasing inequality until organized labor got enough political power to demand and get a bigger share of the fruits of their labors. :--[[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|In the US those benefits peaked during the Great Depression]], when the standard conservative mantra that blames the poor for their poverty did not sell newspapers. US President Franklin Roosevelt taxed the ultra-wealthy like they had never been taxed before or since, and dramatically reduced inequality, which continued to decline until increasing concentration of ownership of the media ushered in a new era of increasing inequality starting with the presidency of Ronald Reagan. :-- [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future#Role of the media|Acemoglu and Johnson insist that technology, including artificial intelligence, can be developed to benefit all. However, but it will not happen without action by the poor and middle class as follows]]: :# Alter the narrative, :# Build countervailing powers [like organized labor], and :# Develop technical, regulatory, and policy solutions to tackle specific aspects of technology’s social bias.<ref>Acemoglu and Johnson (2023, ch. 11).</ref> :-- For more on this, see, e.g., the chapter on [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|Fox, the Great Depression, the Great Recession, and our future]]. === The value of noncommercial news outlets === Some of the problems with the media and their contributions to increasing political polarization and violence are documented in the research summary on "[[Information is a public good: Designing experiments to improve government]]" and in the podcast series available on Wikiversity under "[[:Category:Media reform to improve democracy]]" with leading experts discussing their recommendations. One of the most compelling of the references discussed in that podcast series is Usher and Kim-Leffingwell (2022), who tallied all the federal prosecutions for political corruption in each of the 94 [[w:United States federal judicial district|US federal court district]]s between 2003 and 2019. During that period, the number of journalists in the US fell by a factor of roughly 3 -- between 60 and 70 percent. They found no statistically significant impact on federal prosecutions for political corruption of that decline in the number of journalists. However, each member of the [[w:Institute for Nonprofit News|Institute for Nonprofit News]] (INN) in a federal court district in one year was associated with on average 1.4 additional prosecutions for political corruption the following year. Since federal prosecutions for political corruption averaged roughly 10 per federal court district per year during that period, each member of INN in a federal court district one year was associated with a 14 percent increase in federal prosecutions the following year. This suggests that the major media outlets that had so dramatically reduced their staffs had not substantively reduced the amount of investigative journalism they did. If we assume that the people prosecuted for political corruption also control substantive advertising budgets, then the major media outlets have conflicts of interest in honestly reporting on such. They may report on it if some other organization like a member of INN does the research and they are threatened with a loss of audience from not reporting on it. :'''''Major point''''': You and I benefit, the vast majority of humans on earth benefit, from news reports presumably published by members of INN that contributed to those on average 1.4 additional prosecutions for political corruption estimated by Usher and Kim-Leffingwell (2022). We benefit even if we never heard about the news reports that contributed to those prosecutions. We benefit even if we have never heard of the news outlets that presumably did the investigative journalism behind those additional prosecutions. Why? Because on average those news reports likely deterred other incidents of political corruption, which likely contributed to broadly shared economic growth and the development of new technology that ultimately benefit the vast majority of humanity. Other aspects of this are documented in the research on the impact of [[w:news desert|news desert]]s, which we summarize next. === Costs increase in news deserts=== There's a growing body of research describing what happens when local newspapers die. Perhaps most important, a 2018 research report by Gao et al. reported that the death of a local newspaper was followed by … increases in local tax revenue, averaging $85 per human per year.<ref name = Gao2018>Gao et al. (2018).</ref> That $85 was roughly 13 hundredths of a percent of the 2019 US GDP. That's mentioned in the 2025-07-17 interview with [[Democratic delusions: Fix the media to fix democracy|Natalie Fenton about her new book, ''Democratic Delusions, How the Media Hollows out democracy and What We Can Do About It'']]. One of the most spectacular example of the cost of a news desert is the [[w:City of Bell scandal|Scandal of Bell, California]]. Their local newspaper died around 1999. Roughly a decade later the city was nearly bankrupt in spite of having property tax rates among the highest in the nation. An investigation by the ''[[w:Los Angeles Times|Los Angeles Times]]'' documented that the city manager had a compensation package worth $1.5 million a year, well over double that of the President of the United States. Other senior city officials were similarly well-remunerated. Some of the city officials went to jail over that. Did the city manager decide after 1999, "Wow: The watchdog is dead. Let's have a party"? Malfeasance also increases in business as pollution and workplace accidents increase as does the cost of capital, because investors know their money is not as secure without a local newspaper. That leads to a reduction in investments in new products, services and processes -- slowing economic growth. See "[[Local newspapers limit malfeasance]]", esp. Kim et al. (2021). And executive compensation in increases in nonprofits, so less of what people donate goes to the charitable purpose for which they donated, according to Felix et al. (2024). Also, voter participation and split-ticket voting decline, per Benton (2019) and other references discussed in "[[Information is a public good: Designing experiments to improve government]]". And the ultra-right does better, as noted in [[News from Germany 1900-1945 and implications for today]] and the section on "[[Information is a public good: Designing experiments to improve government#Previous research|Previous research]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]".<ref>Flößer (2024).</ref> The 0.13 percent of GDP savings estimated by Gao et al. (2018) is roughly $120 per human per year. With over 300 million humans in the U.S, that is roughly $40 billion nationwide. {| class="wikitable" |+ Table 1. Costs increase in news deserts |- ! Entity !! What !!Source |- | rowspan=2 |local government || costs incr. 0.13% of GDP || Gao et al. (2018) |- | cost incr. 0.05 - 0.11% of GDP || Baker and Murphy (2026 ) |- | local businesses || pollution & workplace accidents incr., innovation & econ growth decr. || Kim et al. (2021) |- | nonprofits || exec. compensation incr. || Felix et al. (2024) |- | rowspan=2 | elections | voter participation & split-ticket voting decl. || Benton (2019) |- | Ultra-right does better || Flößer (2024) |} === Government subsidies for news === John (1995) documented how in the first half of the nineteenth century the US had more independent newspaper publishers per million population than at any other time or place in human history.<ref>This is discussed in the 2025-06-08 [[Media concentration per Columbia History Professor Richard John|interview with him]], available on Wikiversity under [[:Category:Media reform to improve democracy]], accessed 2026-04-30.</ref> This encouraged literacy and limited political corruption, both of which helped [[The Great American Paradox|the early United States stay together and grow]] while contemporary [[w:New Spain|New Spain]] / [[w:Mexico|Mexico]], fractured, shrank, and stagnated economically. As documented with Figure 1 in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]], that growth catapulted the young United States into its current position of dominance in the international political economy, a position it has been losing since at least 1990 -- or since the Reagan Revolution began in 1981, according to the analysis in the chapter below on [[/Fox, the Great Depression, the Great Recession, and our future/]]. Other countries now have stronger democracies due in part to government subsidies for media in the range of 0.05 and 0.25 percent of GDP with a firewall that limits political interference in the content, according to Neff and Pickard (2024). Table 1 in "[[Information is a public good: Designing experiments to improve government]] compares media subsidies in various places with "other points of reference". McChesney and Nichols (2010, pp. 310-311, note 88) suggested that the relatively high rate of economic growth of the economy in the early US was due in part to postal subsidies under the US [[w:Postal Service Act|Postal Service Act]] of 1792.<ref>See also the Wikiversity article on "[[The Great American Paradox]]", accessed 2026-04-30.</ref> They estimated those subsidies at 0.21 percent of GDP. To improve the current political economy of the US, they recommended subsidies of 0.15 percent of GDP distributed to local news nonprofits on the basis of local elections.<ref>McChesney and Nichols (2021, 2022).</ref> The Wikipedia article on "[[Information is a public good: Designing experiments to improve government]]" documents how some jurisdictions can devote that much money to local news nonprofits by matching what they spend on accounting, advertising, and public relations.<ref>See the section on "[[Information is a public good: Designing experiments to improve government#Sampling units / experimental polities|Sampling units / experimental polities]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]", accessed 2026-04-30.</ref> Pickard (2023) describes three basic strategies for confronting concentrated commercial media power: (1) break them up, (2) regulate them, and (3) create non-commercial, public alternatives. A fourth possibility might be [[w:externality|a graduated tax on income and wealth]] in proportion to the threat that major corporations pose to democracy. One class of noncommercial alternatives that Pickard mentions is local multimedia / Public Media Centers (PMCs) with management split between local journalists and boards, e.g., selected at random from registered voters. A key here is to have the boards selected in a way that cannot be influenced by people with power, whether business or political elites. Picard recommends considering '''six discrete layers''' when discussing PMCs, each of which, he says, must be radically democratised: # funding, # governance, # ascertainment (to determine a community’s ''critical information needs''), # infrastructure (including universal broadband service), # algorithmic (e.g., not allowing companies like Google and Facebook to suppress indexing information the might challenge their hegemony of those markets, [[w:Deep web|treating them like pedophilia and the Islamic State]]), # engagement, involving local communities in making their own news and in communicating their own stories; this is paramount to building trust and the grassroots-level support that this new local journalistic model requires. All this needs to be managed in ways that provide substantive support to news deserts and underserved communities that have long been subjected to various kinds of informational redlining. This might be done by including the proposed PMCs within local libraries staffed by professional journalists, who provide training in media literacy in local schools for children and supervise students producing school newspapers. PMCs could host regular, e.g., monthly events, where local residents could share their concerns with journalist, who would use that input to help prioritize different issues for news coverage. Journalist could also coach local residents in how to research issues and collaborate with journalists in producing news reports that may be better researched and more relevant to local concerns than could be produced without such collaboration. Management of such PMCs might be split between journalists on staff and boards of, e.g., six members selected at random from voter registration rolls serving staggered terms of one year with a new member rotated in every 2 months. Another alternative that could be done in parallel with local PMCs calls for 200 journalists in each US Congressional district funded at $10 billion annually in 2022 dollars, which is just a little under 4 hundredths of one percent of GDP; if such allocations are expressed as fractions of a percent of GDP, they would grow naturally with the economy. (The nominal GDP for the US was roughly $26.1 trillion in 2022.<ref>Johnston and Williamson (2026).</ref> For 2026 it is estimated at $32.4 trillion.<ref>[[w:United States|United States]], accessed 2026-04-30.</ref>) A similar model is the [[w:BBC|BBC]]’s Local Democracy Reporting Service (LDRS), in which the BBC funds journalists to cover the work of local councils and other local public bodies, funded at £8 million per year, which is a little under 2 hundredths of a percent of the [[w:United Kingdom|UK]]'s GDP of £7.27 trillion.<ref>[[w:United Kingdom|United Kingdom]], accessed 2026-04-30.</ref> Pickard (2023) ended by saying, "Today we face a crossroads: technocracy and oligarchy from above or radical democracy and structural reform from below. ... [T]his is not just a journalism crisis: it is a democracy crisis." ==Table of Contents== *[[/Introduction/]] including an exercise, asking all to discuss perceptions of the settlement of ''[[w:Dominion Voting Systems v. Fox News Network|Dominion Voting Systems v. Fox News Network]]'' in a friendly supportive manner with humans with whom they may vehemently disagree, because the alternative could be killing humans over misunderstandings. ===Part I. The media and political economy=== # [[/The impact of the media on political economy since the time of the Pharaohs/]] describes how religious leaders in hierarchical societies prior to [[w:James VI and I|King James of the King James bible]] convinced commoners to live in poverty while giving increasing shares of what they produced so religious and secular elites could live in opulence. During the reign of King James, pamphlets and newspapers began to compete with the church for helping commoners understand their roles in society. This produced the Industrial Revolution and modern democracies. Media consolidation since World War II slowed, then reversed this trend. # [[/Fox, the Great Depression, the Great Recession, and our future/]] describes the unprecedented performance of the US political economy during the presidency of Franklin Roosevelt (FDR), insisting that much of what FDR achieved can be replicated, giving a media system that supports honest discussion of the available evidence. # [[/Media consolidation, social media, and political polarization/]] (Combine from McChesney and Nichols discussing the [[w:Postal Service Act|US Postal Service Act]] of 1792 with [[Media concentration per Columbia History Professor Richard John]], the section on "[[v:Information is a public good: Designing experiments to improve government#Threats from social media|Threats from social media]]" in "[[Information is a public good: Designing experiments to improve government]], and the comments by [[v:Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen that, "the shortest path to a click is anger or hate."]]. ===Part II. The media and war=== # [[/Deterrence without threat/]]: The historical record is clear: Nations that have prepared for war often got war, not peace. This happens for at least two reasons: First, some leaders cannot resist the temptation to use force inappropriately, sometimes clandestinely provoking others to do things that are then denounced as "unprovoked"; sometimes the media environment pushes them to do such. Alternatively, potential adversaries may believe -- or claim -- that you are actually preparing a first strike, and they must move preemptively or lose their ability to retaliate adequately. We can avoid these possibilities with three supportive policies: [a] Legislation that ''prohibits'' projecting force beyond our own borders. [b] Civilian-based defense training in nonviolent noncooperation like what helped Denmark survive Nazi occupation with minimal damage. And [c] a media system that penalizes rather than encourages a bellicose foreign policy. # [[/Responding to a nuclear attack/]]: The ''worst'' response to a nuclear attack would be a nuclear response: The death toll from the 1945 [[w:Atomic bombings of Hiroshima and Nagasaki|Atomic bombings of Hiroshima and Nagasaki]] was estimated at between 150,000 and a quarter of a million. By contrast, simulations of nuclear wars of different magnitudes estimated that between 4 and 95 percent of humanity around the world would starve to death if they did not die of something else sooner. The range depends on whether the war was "limited", e.g., between India and Pakistan, and massive between the US and Russia. (Also add material from [[Nuclear weapons and effective defense]]). # [[/Threats from excessive government secrecy/]] (draft in [https://sanjosepeace.org/restrict-secrecy-more-than-data-collection/ "Restrict secrecy more than data collection"], adding material from [https://kkfi.org/program-episodes/does-us-government-secrecy-threaten-national-security/ Connelly (2023) ''The Declassification Engine: What History Reveals About America's Top Secrets''], [[Wikipedia:Moynihan Commission on Government Secrecy]] and [[1998 Embassy bombings and September 11]]. # [[/Shouting fire in a crowded theater/|Shouting ''fire'' in a crowded theater]]: Legal concerns about "[[w:Shouting fire in a crowded theater|Shouting ''fire'' in a crowded theater]]" date, at least in large part, from the [[w:Supreme Court of the United States|US Supreme Court]] decisions in ''[[w:Schenck v. United States|Schenck v. United States]]'' (1919) and ''[[w: Brandenburg v. Ohio| Brandenburg v. Ohio]]'' (1969). In ''Schenck'' the Court ruled that the government had a right to imprison Schenck and others, because their distribution of fliers encouraging draft resistance presented a [[w:clear and present danger|clear and present danger]] to the efficacy of ongoing military activities during [[w:World War I|World War I]], then in progress. The Court in ''Brandenburg'' held that the government cannot punish inflammatory speech ''unless that speech is "directed to inciting or producing imminent lawless action and is likely to incite or produce such action".'' Some could argue that many uses of military force by the US and Israel since 1948 have violated international law, encouraged by biases in the major US media "directed to inciting or producing imminent lawless action", though it may not be feasible to convince a court of that. Still, it might be useful to simulate such a case in a mock trial like the 1966 [[w:Russell Tribunal|Russell Tribunal]].<ref>Andersen (2006) provides such documentation for several such uses of force. Andersen (2026) and Johnson (2026) organize evidence supporting such claims for the current [[w:Gaza war|Gaza war]], which began with [[w:October 7 attacks|Palestinian attacks 2023-10-07]]. Might, e.g., Palestinians -- or at least Palestinian Americans -- be able to sue the [[w:Anti-Defamation League|Anti-Defamation League]] (ADL), the [[w:AIPAC|American Israel Public Affairs Committee]] (AIPAC), and all the major media outlets in the US for inciting genocide in the current [[w:Gaza war|Gaza war]]? That history includes routine suppression of coverage by the major media especially in the US of routine denial of equal protection of Israeli laws to non-Jews in Israel and under Israeli occupation, including suppression of Israeli violence against nonviolent protestors peaceably assembling and petitioning for a redress of grievances combined with over reporting of Palestinian violence and unquestioning coverage of fraudulent claims of Palestinian violence by Israel and supporters. The suppressions included underreporting of Palestinian nonviolence such as the [[w:2018–2019 Gaza border protests|(2018-2019) Great March of Return]], and suppression of the grievances inspiring such nonviolence such as indefinite detention without charges of thousands of Palestinians, including children, routine destruction of Palestinian property by settlers, confiscation of Palestinian property at gunpoint, closing [[w:Gaza Strip|Gaza]] to international trade, and maintaining Gaza on starvation rations. These routine biases in reporting have been encouraged by charges that more honest reporting would be "[[w:Antisemitism|antisemetic]], according to the ADL and AIPAC. This denial of coverage thereby encouraged Israel to increase the rate of such violations until the [[w:October 7 attacks|2023-10-07 attacks on Israel from Gaza]] unleashed Israeli "retaliations" way out of proportion to the alleged provocation. Sucharov (2022) reported that 69% of American Jews opposed privileging Jews over non-Jews in Israel. Their support of Israel in the current Gaza war is consistent with the media biases documented by Johnson (2026) and others including Andersen (2006, 2026). Regarding whether Israel could achieve anything positive from this war, Samuelson (2025) is skeptical. He summarized quantitative analyses of 60 previous insurgencies. The results including the observation that it is exceedingly difficult to defeat an insurgency without responding to the grievances that support it without force ratios far beyond Israel's resources.</ref> ===Part III. Climate, immigrants, education, public health, and criminal justice=== # [[/Global warming/]] [Summarize research especially on conflicts of interest of major media in honestly reporting on this issue and the research on global warming itself and activities of groups concerned about this issue. Decompose into global population times CO2 equivalents per human.] # [[/Immigrants/]] [Summarize research documenting that [[w:Sanctuary city|sanctuary cities tend to have higher median incomes and no more crime than non-sanctuary jurisdictions]], and some studies report less crime. Moreover economists have documented that immigrants tend to be more entrepreneurial, overrepresented in patent applications, and generally increasing the rate of economic growth. See, e.g., Aghion et al. (2022) ''The power of creative destruction''; Aghion shared the 2025 Nobel Memorial Prize in Economics with two others.] # [[/Education/]] (draft in [[Invest in children]].) # [[/Public health/]] [Draft in [[UN public health data]] to be revised to be consistent with Bezruchka (2023, 2025).] # [[/Substance abuse and addictive behavior/]] (Research cited in "[[Wikipedia:War on drugs]]" insists that the US and the world would have fewer problems with substance abuse and addiction problems with 100 percent public funding for treatment programs and complete decriminalization of possession and use of retail quantities of addictive substances. We would also likely have fewer problems with immigrants, as that would make it harder for the US to intervene in the internal affairs of foreign countries funded off the books, as exposed in the [[w:Iran–Contra affair|Iran–Contra affair]]. See [[w:Alfred W. McCoy|Alfred W. McCoy]] (1972; 3rd ed. 2003) ''The politics of heroin''. Journalist [[w:Gary Webb|Gary Webb]] published similar claims that the US intervention in Nicaragua in the Iran-Contra Affair was funded in part by drug money. The story was officially retracted by the ''San José Mercury News'', and Webb allegedly killed himself with 2 bullets to the head. # [[/Criminal justice/]] (The section on "[[w:United States incarceration rate#Editorial policies of major media|Editorial policies of major media]]" in "[[Wikipedia:United States incarceration rate]]" cites research claiming that within the range range of experience in the US political economy since 1925, the incarceration rate is uncorrelated with crime: It's a function of the public's perception of crime, and that's a function of the media. That suggest that the US would be safer and more prosperous if incarceration policies were driving more by research than by editorial policies of the media. For example, there is also research that says that incarcerees who receive visits are less likely to recidivate, but that evidence is overlooked when convicts are incarcerated substantial distance from their family and friends and when the cost of phone services is substantially higher for incarcerees than among the general pubic. Also, it's known that better educated incarcerees are less likely to recidivate, but it's difficult and maybe impossible for many incarcerees to obtain education in prison.) # [[/Empower women and girls/]] [Cite research claiming that a primary restraint on population growth is empowering women and girls. Empowering women and girls is not just a matter of equity: It is also a means to reduce the threats of global warming, of increasing exposure to animal diseases and other problems that come with unrestrained population growth.] === Continuation === * [[/The evolving media literacy movement/]] to invite others to keep this book current with the evolving understanding of media literacy, how to encourage and promote it and the benefits of doing so. ==See also== * [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools]] ==Notes== {{reflist}} ==Bibliography== * <!--Daron Acemoğlu and Simon Johnson (2023) Power and Progress-->{{cite Q|Q125292212}} * <!--Robin Andersen (2006) A century of media, a century of war-->{{cite Q|Q138795568}} * <!--Robin Andersen (2026-06-02) The Complicit Lens: US Media Coverage of Israel’s Genocide in Gaza-->{{cite Q|Q138796307}} * <!-- Matthew Baker and Dermot Murphy (2026-06-10) "Local News Shortage Leads to $1.1 Billion in Extra Borrowing Costs for Local Governments and Taxpayers"-->{{cite Q|Q141620048}} * <!--Perry Bacon Jr. (2022-10-17) "America Should Spend Billions to Revive Local News"-->{{cite Q|Q139594786}} * <!-- Joshua Benton (9 April 2019). "When local newspapers shrink, fewer people bother to run for mayor". Nieman Foundation for Journalism -->{{cite Q|Q63127216}} * <!--Stephen Bezruchka (2023) Inequality Kills Us All-->{{cite Q|Q136047815}} * <!--Stephen Bezruchka (2025) ''Born Sick in the USA''-->{{cite Q|Q138749292}} * <!--Renée DiResta (2024) Invisible Rulers: The People Who Turn Lies into Reality-->{{cite Q|Q135530439}} * <!--Robert Felix, Joshua A. Khavis, and Mikhail Pevzner (2024) "The effects of local newspaper closures on nonprofits’ executive compensation"-->{{cite Q|Q132730972}} * <!--Maxim Flößer (2024-03-06) "Keine Lokalzeitung -- mehr AfD", Kontext-->{{cite Q|Q125287792}} * <!--Pengjie Gao, Chang Lee, and Dermot Murphy (2018) "Financing Dies in Darkness? The Impact of Newspaper Closures on Public Finance"-->{{cite Q|Q55670016}} * <!--Spencer Graves (2024) "Wikipedia: The most democratic force on earth-->{{cite Q|Q137796922}} * <!--Spencer Graves and Bryan Bailey (2025) "We have to talk", blog at PeaceWorksKC.org-->{{cite Q|Q136126262}} * [[d:Q138038060|Dan Hind and Spencer Graves (2025) "Media Reform Coalition challenges anti-democratic media bias in the UK" on Wikiversity]]. * <!--Richard R. John (1995) Spreading the News: The American Postal System from Franklin to Morse-->{{cite Q|Q54641943}} * <!--Adam H. Johnson (2026-04-21) How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza-->{{cite Q|Q140073447}} * <!--Louis Johnston and Samuel H. Williamson, "What Was the U.S. GDP Then?" MeasuringWorth, 2026-->{{cite Q|Q56881105}} * <!-- Min Kim, Derrald Stice, Han Stice, and Roger M. White (2021) "Stop the presses! Or wait, we might need them: Firm responses to local newspaper closures and layoffs"-->{{cite Q|Q132459373}} * <!-- Robert W. McChesney; John Nichols (2010). The Death and Life of American Journalism (Bold Type Books) -->{{cite Q|Q104888067}}. * <!-- Robert W. McChesney; John Nichols (2021). "The Local Journalism Initiative: a proposal to protect and extend democracy". Columbia Journalism Review, 30 November 2021 -->{{cite Q|Q109978060}} * <!-- Robert W. McChesney; John Nichols (2022), To Protect and Extend Democracy, Recreate Local News Media (PDF), FreePress.net (updated 25 January 2022) -->{{cite Q|Q109978337|access-date=2024-06-23}} * <!--Alfred W. McCoy (2003-05-01) The politics of heroin : CIA complicity in the global drug trade : Afghanistan, Southeast Asia, Central America, Colombia-->{{cite Q|Q141317509}} * <!--Joel Mokyr (2017) A Culture of Growth: The Origins of the Modern Economy (Graz Schumpeter Lectures; Princeton University Press)-->{{cite Q|Q136118590}} * <!--Neff and Pickard (2024) "Funding Democracy: Public Media and Democratic Health in 33 Countries"-->{{cite Q|Q131468289}} * [[d:Q131398359|Victor Pickard (2020) ''Democracy without journalism? : confronting the misinformation society'' (Oxford U. Pr.)]]. * <!-- Victor Pickard (2023-05-12) "Another Media System is Possible: Ripping Open the Overton Window, from Platforms to Public Broadcasting"-->{{cite Q|Q131398460}} * <!--Doug Samuelson (2025) Assessing Israel’s Approach in Gaza-->{{cite Q|Q138843324}} * [[d:Q138037937|Dean Starkman and Spencer Graves (2025) "Dean Starkman and the watchdog that didn't bark anglais" on Wikiversity]]. * <!--Mira Sucharov (2022) Do American Jews Really Know What 'Zionist' Means?-->{{cite Q|Q125903777}} * [[d:Q134715465|Nikki Usher and Sanghoon Kim-Leffingwell (2022) "How Loud Does the Watchdog Bark? A Reconsideration of Local Journalism, News Non-profits, and Political Corruption", ''SSRN Electronic Journal'']]. * [[d:Q61013892|Horacio Verbitsky (1997) ''Un mundo sin periodistas'' (in Spanish: A world without journalists; Editorial Sudamericana)]]. [[Category:Communication]] [[Category:Political science]] [[Category:Law]] [[Category:Psychology]] [[Category:Sociology]] [[Category:Education]] [[Category:Economics]] [[Category:Media Literacy and You]] [[Category:Freedom and abundance]] <!-- https://en.wikiversity.org/wiki/Category_Review --> eo4ahwwtuhc79ks59mwxmo0pisbsj3n 2835412 2835401 2026-10-02T01:39:50Z DavidMCEddy 218607 add ref Greenwood 2835412 wikitext text/x-wiki [[File:Pharoah - James VI and I - Trump.png|thumb|Religious and media leaders from the time of the Pharaohs convinced common folk to give increasing shares of what they produced to elites.]] :''This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.'' == Invitation to edit this book == You, dear reader, are invited to contribute questions, ideas and citations to support or refute claims made in this book possibly adding chapters. Wikiversity like other Wikimedia Foundation Projects invites humans to [[w:Wikipedia:Be bold|“be bold but not reckless,”]] while writing from a [[Wikiversity:Disclosures|neutral point of view]], [[Wikiversity:Cite sources|citing credible sources]]. Others are invited to change or revert what you wrote. What stays tends to be written from a neutral point of view citing credible sources. If someone reverts your edit or you have a question, take it to the ''[[Wikiversity:FAQ|''''“Discuss”'''' page]]'' associated with the specific Wikiversity page most related to your concerns. Those who teach media literacy are encouraged to invite their students to debate and revise the contents of this book. Doing so would build on a tradition of [[:w:Wikipedia:Student assignments|instructors requiring students to edit wikipedia article(s).]] Editing [[:w:Wikipedia|Wikipedia]] and other [[:w:Wikimedia Foundation|Wikimedia Foundation]] projects like this book is itself an exercise in media literacy: :''Central tenets of media literacy might include writing from a neutral point of view citing credible sources and engaging others, some of whom may disagree, in civil, supportive conversations about what can and cannot be said based on a reasonable evaluation of the available evidence. Wikimedia rules invite contributors to do just that, encouraging them to “be bold but not reckless,” contributing revisions written from a neutral point of view, citing credible sources -- and raising other questions and concerns on the ''''“Discuss”'''' page associated with the specific Wikiversity page most related to your concerns, as mentioned above.''<ref>For more on this, see Graves (2024).</ref> == Text and self-help book and point of discuss == This book is intended both as a text and self-help book and as a point of discussion considering four levels of media literacy: :1. '''Think before you share''': Follow the money. Every media organization sells changes in audience behaviors to those who control much of their money. Major media everywhere promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to convince the public to give increasing shares of what they produce to elites to "protect them from designated evil others." To counter this, DiResta (2024, p. 335) recommends, "Think before you share." :2. '''Look for information to contradict preconceptions''' (Disconfirmation bias): [[w:Information is a public good: Designing experiments to improve government#Previous research|Virtually everyone]] (a) thinks they know more than they do ([[w:Overconfidence effect|overconfidence effect]]), and (b) prefers information and sources consistent with preconceptions ([[w:Confirmation bias|confirmation bias]]). The major media everywhere exploit this to please those who control most of the money for the media. Humans can counter this by searching for sources to help us understand our designated enemies. ''If we cannot explain circumstances under which we could see ourselves doing what we see our designated enemies doing, we have not looked hard enough.'' :3. '''Talk''': Push ourselves to have friendly supportive conversations with others with whom we may vehemently disagree, seeking common ground, agreeing to disagree agreeably where we differ, and building collaboration on areas of common concern.<ref>Graves and Bailey (2025).</ref> :4. '''Teach''': Humans who develop skills in the first three levels can leverage that knowledge in helping others acquire those skills. If each one teaches two<ref>"[[:w:Each one teach one|Each one teach one]]" is an African-American proverb from the time of legalized slavery. However, if each one teaches only one, the growth in literacy will only be linear. Having "each one teaching two", on average, unleashes the power of doubling and [[:w:exponential growth|exponential growth]], which has the potential of educating the entirety of humanity in a reasonable period of time -- namely after 33 doublings starting from one.</ref> in a certain period of time, that time period becomes a [[:w:Doubling time|doubling time]]. Ten doublings is a thousand -- actually 1,024 to be precise.<ref>2 time 2 = 4 times 2 = 8 times 2 = 16 times 2 = 32 times 2 = 64 times 2 = 128 times 2 = 256 times 2 = 512 times 2 = 1024: That's 10 doublings, as anyone with a modest understanding of modern digital [[:w:computer|computer]]s will tell you.</ref> Twenty doublings become a million. Thirty doublings become a billion. Three more doublings become 8 billion, the [[:w:World population|world population]] as of approximately 2022-11-15.<ref>This book uses dates in [[:w:ISO 8601|ISO 8601]], YYYY-MM-DD, when convenient.</ref> Many organizations, including several United Nations agencies and the [[Yonty Friesem on media education|Media Education Lab]], have been working on [[w:media literacy|media literacy]] for decades and have trained many.<ref>''[[Wikibooks:Antiracist Activism for Teachers and Students]]'' includes a chapter on [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools|Media Literacy In Schools]].</ref> This book is being written hoping to increase the effectiveness and accelerate the rate of growth in media literacy and thereby accelerate progress against many of the most pressing issues facing humanity today.<ref>[[w:Nolan Higdon|Nolan Higdon]] and Spencer Graves discussed marketing media literacy in a "[[:Category:Media reform to improve democracy|Media & Democracy]]" episode on, "[[Media literacy and why you should care]]".</ref> Much of this book is a [[w:Monograph|research monograph]] summarizing research that seems to have been underreported by the major media to avoid offending people who control most of the money for the media. These research results seem to be central to major political divisions. Each chapter ends in exercises to help the reader practice media literacy skills and have fun doing it. Remember: :''I am entitled to my [[Wiktionary:cockamamie|cockamamie]] ideas, and you are entitled to yours.'' Humor is important but must be offered in a way that does not offend others. If others are offended, they may be less interested in dialogue. The term "cockamamie" is used here, hoping that this style of [[w:Self-deprecation|self-deprecation]] might be more inviting for dialogue. ''Never say, "You're wrong." Instead, ask, "May I offer a contrary perspective?" Or "May I share with you another view that I've heard?"'' Much of the information in this book seems to have been largely overlooked and perhaps suppressed, apparently because it would either offend people who control substantial portions of the money for the media our would increase the cost of producing news; see the brief discussion of conflicts of interest by the major media in the next "Key claims" section. ==Key claims== * ''Primary drivers of every major conflict include differences between the media or difference in interpretation that the different parties find credible''. :-- This works, because everything we think we know is coded in systems of connections between neurons in our brains. These systems are more unique than fingerprints and evolve over time. The words we use do not mean the same to two different humans nor even to the same human at different points in time. In many cases these differences are inconsequential. ''Sometimes they are fatal.''<ref>Graves and Bailey (2026).</ref> :-- ''[[w:Social constructionism|Show me someone who knows the truth]], and I will show you someone who is dangerous'' -- especially during war or any other situation where humans may be moved to violence encouraged by their belief system.<ref>[[w:Collateral damage|Collateral damage]] that "they" commit proves to "us" that "they" are subhuman or at best criminally misled and must be resisted by any means necessary. By contrast, collateral damage that "we" commit is unfortunate but necessary.</ref> * ''The major media everywhere have [[w:Conflict of interest|conflicts of interest ]] in honestly reporting on [[v:Information is a public good per communications prof Pickard|anything that might offend anyone who controls large portions of the money for the media]].''<ref>Pickard and Graves (2025), accessed 2026-02-08; Pickard (2020).</ref> :--[[v:Media Reform Coalition challenges anti-democratic media bias in the UK|British journalist and media reform advocate Dan Hind]] said that the content produced by the [[w:BBC|BBC]] was frivolous, soap opera stuff, because leading media personalities know very little about issues of substance and believe "they might get in trouble if" they produced anything serious. Similar analyses seem to apply to the major media everywhere<ref>Hind and Graves (2025), accessed 2026-02-09.</ref> but may not apply to non-profit and local media, which seem more likely to produce [[w:Investigative journalism|investigative]] / [[v:Dean Starkman and the watchdog that didn't bark|accountability journalism]]:<ref>Usher and Kim-Leffingwell (2022); see also Starkman and Graves (2025), accessed 2026-02-09.</ref> [[w:Watchdog journalism|Watchdogs]] tend to protect the people who feed them. Argentine journalist [[w:Horacio Verbitsky|Horacio Verbitsky]] said, "Journalism is disseminating information that someone does not want known; the rest is [[w:propaganda|propaganda]]."<ref>p. 16 in Verbitsky (1997); English translation from [[Wikiquote:Horacio Verbitsky]], accessed 2026-02-09.</ref> * ''The major media everywhere create the stage upon which politicians read their lines.'' :-- Major media promote ''entrepreneurs of hate''<ref>Mokyr (2017, p. 60).</ref> to make it easier for elites to pick everyone else's pockets. This is particularly effective with for-profit social media, which make money herding their audience into echo chambers, where erroneous preconceptions are reinforced, increasing political polarization and violence. [[Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen said]], "The shortest path to a click is anger or hate." A leading expert on for-profit social media is Renée DiResta,<ref>DiResta (2024).</ref> whose research documents how lies spread on social media threaten public health and prepped a small army of humans throughout the 2020 US presidential election cycle to believe that there were major deficiencies in the integrity of US election procedures. When Trump lost, he was able to recruit [[w:January 6 United States Capitol attack|a crowd to attack the capitol on January 6, 2021]]. Social media influencers made so much money spreading lies that it seemed profitable for them to file frivolous lawsuits ([[w:Strategic lawsuit against public participation|SLAPP]]), hoping that DiResta's legal bills would convince her to stop trying to expose their lies. After Republicans regained control of the US House in 2022, they subpoenaed her, claiming she had taken orders from the "[[w:Deep state|deep state]]" to tell Facebook to censor conservatives. [[Managing the good and the evils of social media|When interviewed for ''Media & Democracy'', she reported legal bills of $7 million]]. :-- The social psychology behind this phenomenon exploits especially [[w:confirmation bias|confirmation bias]]. It has contributed to [[Media Literacy and You/Media consolidation, social media, and political polarization|the dramatic increase in political polarization and violence worldwide]], especially since the end of the [[w:Fairness doctrine|Fairness doctrine]] in 1987. :-- Democracy may be best protected by local news nonprofits, managed jointly by journalists and boards selected at random from registered voters, according to Pickard (2023), discussed in the section below on "[[Media Literacy and You#Government subsidies for news|Government subsidies for news]]". :-- Their selection of acceptable topics for news and entertainment create and maintain the "[[w:Overton window|Overton window]]", which is the range of acceptable political discourse. For example, in early 1964, US President [[w:Lyndon B. Johnson|Lyndon Johnson]] understood that he could lose the 1964 presidential election that year if he were seen to be soft on communism. His response was to clandestinely provoke an attack on US naval vessels in the Gulf of Tonkin, which he could then denounce as "unprovoked". During a dark and stormy night 1964-08-04 the [[w:USS Maddox (DD-731)|USS ''Maddox'']] and [[w:USS Turner Joy|''Turner Joy'']] spent a couple of hours "defending themselves" against radar snow, then [[w:Gulf of Tonkin incident|reported that they had sunk two attacking North Vietnamese torpedo boats]]; subsequent investigations found no evidence of the reported attacks. That incident was used to justify the [[w:Gulf of Tonkin Resolution|Gulf of Tonkin Resolution]], with only two dissenting votes in the US Congress: Those two dissenters were defeated in their next reelection campaigns, illustrating the point that ::''the major media create the environment in which many politicians cannot get elected without betraying the nation.'' :-- Nick Hart,<ref name=Hart><!--Nick Hart-->{{cite Q|Q135663983}}</ref> President and CEO of the Data Foundation,<ref><!--Data Foundation-->{{cite Q|Q134705118}}</ref> noted that President Trump in his first term signed the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] of 2019, which was bipartisan legislation ostensibly mandating evidence-informed public policy.<ref>Hart mentioned the [[w:Foundations for Evidence-Based Policymaking Act|Foundations for Evidence-Based Policymaking Act]] when he was interviewed for [[Evidence-informed public policy|"Media & Democracy" 2025-07-31]].</ref> Tragically, the record since 2019 suggests that, ::''The US Congress is rarely allowed to consider solid research suppressed by the major media.'' * ''The development of technology is never neutral in its impact on inequality but is driven to benefit people with power.''<ref>Acemoglu and Johnson (2023)</ref>. :-- [[Media Literacy and You/The impact of the media on political economy since the time of the Pharaohs|Improvements in agricultural technology from pre-history to the time of King James of the King James bible were managed to benefit elites.]] Then pamphlets and newspapers began to appear, the head of state stopped granting as many monopolies, and commoners began getting permission to become entrepreneurs. That transformed economic stagnation into growth in GDP per capita adjusted for inflation, initiating the [[w:Industrial Revolution|Industrial Revolution]], as documented in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]]. It also led to increasing inequality until organized labor got enough political power to demand and get a bigger share of the fruits of their labors. :--[[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|In the US those benefits peaked during the Great Depression]], when the standard conservative mantra that blames the poor for their poverty did not sell newspapers. US President Franklin Roosevelt taxed the ultra-wealthy like they had never been taxed before or since, and dramatically reduced inequality, which continued to decline until increasing concentration of ownership of the media ushered in a new era of increasing inequality starting with the presidency of Ronald Reagan. :-- [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future#Role of the media|Acemoglu and Johnson insist that technology, including artificial intelligence, can be developed to benefit all. However, but it will not happen without action by the poor and middle class as follows]]: :# Alter the narrative, :# Build countervailing powers [like organized labor], and :# Develop technical, regulatory, and policy solutions to tackle specific aspects of technology’s social bias.<ref>Acemoglu and Johnson (2023, ch. 11).</ref> :-- For more on this, see, e.g., the chapter on [[Media Literacy and You/Fox, the Great Depression, the Great Recession, and our future|Fox, the Great Depression, the Great Recession, and our future]]. === The value of noncommercial news outlets === Some of the problems with the media and their contributions to increasing political polarization and violence are documented in the research summary on "[[Information is a public good: Designing experiments to improve government]]" and in the podcast series available on Wikiversity under "[[:Category:Media reform to improve democracy]]" with leading experts discussing their recommendations. One of the most compelling of the references discussed in that podcast series is Usher and Kim-Leffingwell (2022), who tallied all the federal prosecutions for political corruption in each of the 94 [[w:United States federal judicial district|US federal court district]]s between 2003 and 2019. During that period, the number of journalists in the US fell by a factor of roughly 3 -- between 60 and 70 percent. They found no statistically significant impact on federal prosecutions for political corruption of that decline in the number of journalists. However, each member of the [[w:Institute for Nonprofit News|Institute for Nonprofit News]] (INN) in a federal court district in one year was associated with on average 1.4 additional prosecutions for political corruption the following year. Since federal prosecutions for political corruption averaged roughly 10 per federal court district per year during that period, each member of INN in a federal court district one year was associated with a 14 percent increase in federal prosecutions the following year. This suggests that the major media outlets that had so dramatically reduced their staffs had not substantively reduced the amount of investigative journalism they did. If we assume that the people prosecuted for political corruption also control substantive advertising budgets, then the major media outlets have conflicts of interest in honestly reporting on such. They may report on it if some other organization like a member of INN does the research and they are threatened with a loss of audience from not reporting on it. :'''''Major point''''': You and I benefit, the vast majority of humans on earth benefit, from news reports presumably published by members of INN that contributed to those on average 1.4 additional prosecutions for political corruption estimated by Usher and Kim-Leffingwell (2022). We benefit even if we never heard about the news reports that contributed to those prosecutions. We benefit even if we have never heard of the news outlets that presumably did the investigative journalism behind those additional prosecutions. Why? Because on average those news reports likely deterred other incidents of political corruption, which likely contributed to broadly shared economic growth and the development of new technology that ultimately benefit the vast majority of humanity. Other aspects of this are documented in the research on the impact of [[w:news desert|news desert]]s, which we summarize next. === Costs increase in news deserts=== There's a growing body of research describing what happens when local newspapers die. Perhaps most important, a 2018 research report by Gao et al. reported that the death of a local newspaper was followed by … increases in local tax revenue, averaging $85 per human per year.<ref name = Gao2018>Gao et al. (2018).</ref> That $85 was roughly 13 hundredths of a percent of the 2019 US GDP. That's mentioned in the 2025-07-17 interview with [[Democratic delusions: Fix the media to fix democracy|Natalie Fenton about her new book, ''Democratic Delusions, How the Media Hollows out democracy and What We Can Do About It'']]. One of the most spectacular example of the cost of a news desert is the [[w:City of Bell scandal|Scandal of Bell, California]]. Their local newspaper died around 1999. Roughly a decade later the city was nearly bankrupt in spite of having property tax rates among the highest in the nation. An investigation by the ''[[w:Los Angeles Times|Los Angeles Times]]'' documented that the city manager had a compensation package worth $1.5 million a year, well over double that of the President of the United States. Other senior city officials were similarly well-remunerated. Some of the city officials went to jail over that. Did the city manager decide after 1999, "Wow: The watchdog is dead. Let's have a party"? Malfeasance also increases in business as pollution and workplace accidents increase as does the cost of capital, because investors know their money is not as secure without a local newspaper. That leads to a reduction in investments in new products, services and processes -- slowing economic growth. See "[[Local newspapers limit malfeasance]]", esp. Kim et al. (2021). And executive compensation in increases in nonprofits, so less of what people donate goes to the charitable purpose for which they donated, according to Felix et al. (2024). Also, voter participation and split-ticket voting decline, per Benton (2019) and other references discussed in "[[Information is a public good: Designing experiments to improve government]]". And the ultra-right does better, as noted in [[News from Germany 1900-1945 and implications for today]] and the section on "[[Information is a public good: Designing experiments to improve government#Previous research|Previous research]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]".<ref>Flößer (2024).</ref> The 0.13 percent of GDP savings estimated by Gao et al. (2018) is roughly $120 per human per year. With over 300 million humans in the U.S, that is roughly $40 billion nationwide. {| class="wikitable" |+ Table 1. Costs increase in news deserts |- ! Entity !! What !!Source |- | rowspan=4 |local government || costs +0.13% of GDP || Gao et al. (2018) |- | costs +0.05 - 0.11% of GDP || Baker and Murphy (2026 ) |- | pol. corruption charges +6.9% || Greenwood (2026) |- | pol. corruption charges +15% per member of INN || Usher and Kim-Leffingwell (2022) |- | local businesses || pollution & workplace accidents incr., innovation & econ growth decr. || Kim et al. (2021) |- | nonprofits || exec. compensation incr. || Felix et al. (2024) |- | rowspan=2 | elections | voter participation & split-ticket voting decl. || Benton (2019) |- | Ultra-right does better || Flößer (2024) |} === Government subsidies for news === John (1995) documented how in the first half of the nineteenth century the US had more independent newspaper publishers per million population than at any other time or place in human history.<ref>This is discussed in the 2025-06-08 [[Media concentration per Columbia History Professor Richard John|interview with him]], available on Wikiversity under [[:Category:Media reform to improve democracy]], accessed 2026-04-30.</ref> This encouraged literacy and limited political corruption, both of which helped [[The Great American Paradox|the early United States stay together and grow]] while contemporary [[w:New Spain|New Spain]] / [[w:Mexico|Mexico]], fractured, shrank, and stagnated economically. As documented with Figure 1 in the chapter below on [[/The impact of the media on political economy since the time of the Pharaohs/]], that growth catapulted the young United States into its current position of dominance in the international political economy, a position it has been losing since at least 1990 -- or since the Reagan Revolution began in 1981, according to the analysis in the chapter below on [[/Fox, the Great Depression, the Great Recession, and our future/]]. Other countries now have stronger democracies due in part to government subsidies for media in the range of 0.05 and 0.25 percent of GDP with a firewall that limits political interference in the content, according to Neff and Pickard (2024). Table 1 in "[[Information is a public good: Designing experiments to improve government]] compares media subsidies in various places with "other points of reference". McChesney and Nichols (2010, pp. 310-311, note 88) suggested that the relatively high rate of economic growth of the economy in the early US was due in part to postal subsidies under the US [[w:Postal Service Act|Postal Service Act]] of 1792.<ref>See also the Wikiversity article on "[[The Great American Paradox]]", accessed 2026-04-30.</ref> They estimated those subsidies at 0.21 percent of GDP. To improve the current political economy of the US, they recommended subsidies of 0.15 percent of GDP distributed to local news nonprofits on the basis of local elections.<ref>McChesney and Nichols (2021, 2022).</ref> The Wikipedia article on "[[Information is a public good: Designing experiments to improve government]]" documents how some jurisdictions can devote that much money to local news nonprofits by matching what they spend on accounting, advertising, and public relations.<ref>See the section on "[[Information is a public good: Designing experiments to improve government#Sampling units / experimental polities|Sampling units / experimental polities]]" in the Wikiversity article on "[[Information is a public good: Designing experiments to improve government]]", accessed 2026-04-30.</ref> Pickard (2023) describes three basic strategies for confronting concentrated commercial media power: (1) break them up, (2) regulate them, and (3) create non-commercial, public alternatives. A fourth possibility might be [[w:externality|a graduated tax on income and wealth]] in proportion to the threat that major corporations pose to democracy. One class of noncommercial alternatives that Pickard mentions is local multimedia / Public Media Centers (PMCs) with management split between local journalists and boards, e.g., selected at random from registered voters. A key here is to have the boards selected in a way that cannot be influenced by people with power, whether business or political elites. Picard recommends considering '''six discrete layers''' when discussing PMCs, each of which, he says, must be radically democratised: # funding, # governance, # ascertainment (to determine a community’s ''critical information needs''), # infrastructure (including universal broadband service), # algorithmic (e.g., not allowing companies like Google and Facebook to suppress indexing information the might challenge their hegemony of those markets, [[w:Deep web|treating them like pedophilia and the Islamic State]]), # engagement, involving local communities in making their own news and in communicating their own stories; this is paramount to building trust and the grassroots-level support that this new local journalistic model requires. All this needs to be managed in ways that provide substantive support to news deserts and underserved communities that have long been subjected to various kinds of informational redlining. This might be done by including the proposed PMCs within local libraries staffed by professional journalists, who provide training in media literacy in local schools for children and supervise students producing school newspapers. PMCs could host regular, e.g., monthly events, where local residents could share their concerns with journalist, who would use that input to help prioritize different issues for news coverage. Journalist could also coach local residents in how to research issues and collaborate with journalists in producing news reports that may be better researched and more relevant to local concerns than could be produced without such collaboration. Management of such PMCs might be split between journalists on staff and boards of, e.g., six members selected at random from voter registration rolls serving staggered terms of one year with a new member rotated in every 2 months. Another alternative that could be done in parallel with local PMCs calls for 200 journalists in each US Congressional district funded at $10 billion annually in 2022 dollars, which is just a little under 4 hundredths of one percent of GDP; if such allocations are expressed as fractions of a percent of GDP, they would grow naturally with the economy. (The nominal GDP for the US was roughly $26.1 trillion in 2022.<ref>Johnston and Williamson (2026).</ref> For 2026 it is estimated at $32.4 trillion.<ref>[[w:United States|United States]], accessed 2026-04-30.</ref>) A similar model is the [[w:BBC|BBC]]’s Local Democracy Reporting Service (LDRS), in which the BBC funds journalists to cover the work of local councils and other local public bodies, funded at £8 million per year, which is a little under 2 hundredths of a percent of the [[w:United Kingdom|UK]]'s GDP of £7.27 trillion.<ref>[[w:United Kingdom|United Kingdom]], accessed 2026-04-30.</ref> Pickard (2023) ended by saying, "Today we face a crossroads: technocracy and oligarchy from above or radical democracy and structural reform from below. ... [T]his is not just a journalism crisis: it is a democracy crisis." ==Table of Contents== *[[/Introduction/]] including an exercise, asking all to discuss perceptions of the settlement of ''[[w:Dominion Voting Systems v. Fox News Network|Dominion Voting Systems v. Fox News Network]]'' in a friendly supportive manner with humans with whom they may vehemently disagree, because the alternative could be killing humans over misunderstandings. ===Part I. The media and political economy=== # [[/The impact of the media on political economy since the time of the Pharaohs/]] describes how religious leaders in hierarchical societies prior to [[w:James VI and I|King James of the King James bible]] convinced commoners to live in poverty while giving increasing shares of what they produced so religious and secular elites could live in opulence. During the reign of King James, pamphlets and newspapers began to compete with the church for helping commoners understand their roles in society. This produced the Industrial Revolution and modern democracies. Media consolidation since World War II slowed, then reversed this trend. # [[/Fox, the Great Depression, the Great Recession, and our future/]] describes the unprecedented performance of the US political economy during the presidency of Franklin Roosevelt (FDR), insisting that much of what FDR achieved can be replicated, giving a media system that supports honest discussion of the available evidence. # [[/Media consolidation, social media, and political polarization/]] (Combine from McChesney and Nichols discussing the [[w:Postal Service Act|US Postal Service Act]] of 1792 with [[Media concentration per Columbia History Professor Richard John]], the section on "[[v:Information is a public good: Designing experiments to improve government#Threats from social media|Threats from social media]]" in "[[Information is a public good: Designing experiments to improve government]], and the comments by [[v:Facebook whistleblower Frances Haugen says|Facebook whistleblower Frances Haugen that, "the shortest path to a click is anger or hate."]]. ===Part II. The media and war=== # [[/Deterrence without threat/]]: The historical record is clear: Nations that have prepared for war often got war, not peace. This happens for at least two reasons: First, some leaders cannot resist the temptation to use force inappropriately, sometimes clandestinely provoking others to do things that are then denounced as "unprovoked"; sometimes the media environment pushes them to do such. Alternatively, potential adversaries may believe -- or claim -- that you are actually preparing a first strike, and they must move preemptively or lose their ability to retaliate adequately. We can avoid these possibilities with three supportive policies: [a] Legislation that ''prohibits'' projecting force beyond our own borders. [b] Civilian-based defense training in nonviolent noncooperation like what helped Denmark survive Nazi occupation with minimal damage. And [c] a media system that penalizes rather than encourages a bellicose foreign policy. # [[/Responding to a nuclear attack/]]: The ''worst'' response to a nuclear attack would be a nuclear response: The death toll from the 1945 [[w:Atomic bombings of Hiroshima and Nagasaki|Atomic bombings of Hiroshima and Nagasaki]] was estimated at between 150,000 and a quarter of a million. By contrast, simulations of nuclear wars of different magnitudes estimated that between 4 and 95 percent of humanity around the world would starve to death if they did not die of something else sooner. The range depends on whether the war was "limited", e.g., between India and Pakistan, and massive between the US and Russia. (Also add material from [[Nuclear weapons and effective defense]]). # [[/Threats from excessive government secrecy/]] (draft in [https://sanjosepeace.org/restrict-secrecy-more-than-data-collection/ "Restrict secrecy more than data collection"], adding material from [https://kkfi.org/program-episodes/does-us-government-secrecy-threaten-national-security/ Connelly (2023) ''The Declassification Engine: What History Reveals About America's Top Secrets''], [[Wikipedia:Moynihan Commission on Government Secrecy]] and [[1998 Embassy bombings and September 11]]. # [[/Shouting fire in a crowded theater/|Shouting ''fire'' in a crowded theater]]: Legal concerns about "[[w:Shouting fire in a crowded theater|Shouting ''fire'' in a crowded theater]]" date, at least in large part, from the [[w:Supreme Court of the United States|US Supreme Court]] decisions in ''[[w:Schenck v. United States|Schenck v. United States]]'' (1919) and ''[[w: Brandenburg v. Ohio| Brandenburg v. Ohio]]'' (1969). In ''Schenck'' the Court ruled that the government had a right to imprison Schenck and others, because their distribution of fliers encouraging draft resistance presented a [[w:clear and present danger|clear and present danger]] to the efficacy of ongoing military activities during [[w:World War I|World War I]], then in progress. The Court in ''Brandenburg'' held that the government cannot punish inflammatory speech ''unless that speech is "directed to inciting or producing imminent lawless action and is likely to incite or produce such action".'' Some could argue that many uses of military force by the US and Israel since 1948 have violated international law, encouraged by biases in the major US media "directed to inciting or producing imminent lawless action", though it may not be feasible to convince a court of that. Still, it might be useful to simulate such a case in a mock trial like the 1966 [[w:Russell Tribunal|Russell Tribunal]].<ref>Andersen (2006) provides such documentation for several such uses of force. Andersen (2026) and Johnson (2026) organize evidence supporting such claims for the current [[w:Gaza war|Gaza war]], which began with [[w:October 7 attacks|Palestinian attacks 2023-10-07]]. Might, e.g., Palestinians -- or at least Palestinian Americans -- be able to sue the [[w:Anti-Defamation League|Anti-Defamation League]] (ADL), the [[w:AIPAC|American Israel Public Affairs Committee]] (AIPAC), and all the major media outlets in the US for inciting genocide in the current [[w:Gaza war|Gaza war]]? That history includes routine suppression of coverage by the major media especially in the US of routine denial of equal protection of Israeli laws to non-Jews in Israel and under Israeli occupation, including suppression of Israeli violence against nonviolent protestors peaceably assembling and petitioning for a redress of grievances combined with over reporting of Palestinian violence and unquestioning coverage of fraudulent claims of Palestinian violence by Israel and supporters. The suppressions included underreporting of Palestinian nonviolence such as the [[w:2018–2019 Gaza border protests|(2018-2019) Great March of Return]], and suppression of the grievances inspiring such nonviolence such as indefinite detention without charges of thousands of Palestinians, including children, routine destruction of Palestinian property by settlers, confiscation of Palestinian property at gunpoint, closing [[w:Gaza Strip|Gaza]] to international trade, and maintaining Gaza on starvation rations. These routine biases in reporting have been encouraged by charges that more honest reporting would be "[[w:Antisemitism|antisemetic]], according to the ADL and AIPAC. This denial of coverage thereby encouraged Israel to increase the rate of such violations until the [[w:October 7 attacks|2023-10-07 attacks on Israel from Gaza]] unleashed Israeli "retaliations" way out of proportion to the alleged provocation. Sucharov (2022) reported that 69% of American Jews opposed privileging Jews over non-Jews in Israel. Their support of Israel in the current Gaza war is consistent with the media biases documented by Johnson (2026) and others including Andersen (2006, 2026). Regarding whether Israel could achieve anything positive from this war, Samuelson (2025) is skeptical. He summarized quantitative analyses of 60 previous insurgencies. The results including the observation that it is exceedingly difficult to defeat an insurgency without responding to the grievances that support it without force ratios far beyond Israel's resources.</ref> ===Part III. Climate, immigrants, education, public health, and criminal justice=== # [[/Global warming/]] [Summarize research especially on conflicts of interest of major media in honestly reporting on this issue and the research on global warming itself and activities of groups concerned about this issue. Decompose into global population times CO2 equivalents per human.] # [[/Immigrants/]] [Summarize research documenting that [[w:Sanctuary city|sanctuary cities tend to have higher median incomes and no more crime than non-sanctuary jurisdictions]], and some studies report less crime. Moreover economists have documented that immigrants tend to be more entrepreneurial, overrepresented in patent applications, and generally increasing the rate of economic growth. See, e.g., Aghion et al. (2022) ''The power of creative destruction''; Aghion shared the 2025 Nobel Memorial Prize in Economics with two others.] # [[/Education/]] (draft in [[Invest in children]].) # [[/Public health/]] [Draft in [[UN public health data]] to be revised to be consistent with Bezruchka (2023, 2025).] # [[/Substance abuse and addictive behavior/]] (Research cited in "[[Wikipedia:War on drugs]]" insists that the US and the world would have fewer problems with substance abuse and addiction problems with 100 percent public funding for treatment programs and complete decriminalization of possession and use of retail quantities of addictive substances. We would also likely have fewer problems with immigrants, as that would make it harder for the US to intervene in the internal affairs of foreign countries funded off the books, as exposed in the [[w:Iran–Contra affair|Iran–Contra affair]]. See [[w:Alfred W. McCoy|Alfred W. McCoy]] (1972; 3rd ed. 2003) ''The politics of heroin''. Journalist [[w:Gary Webb|Gary Webb]] published similar claims that the US intervention in Nicaragua in the Iran-Contra Affair was funded in part by drug money. The story was officially retracted by the ''San José Mercury News'', and Webb allegedly killed himself with 2 bullets to the head. # [[/Criminal justice/]] (The section on "[[w:United States incarceration rate#Editorial policies of major media|Editorial policies of major media]]" in "[[Wikipedia:United States incarceration rate]]" cites research claiming that within the range range of experience in the US political economy since 1925, the incarceration rate is uncorrelated with crime: It's a function of the public's perception of crime, and that's a function of the media. That suggest that the US would be safer and more prosperous if incarceration policies were driving more by research than by editorial policies of the media. For example, there is also research that says that incarcerees who receive visits are less likely to recidivate, but that evidence is overlooked when convicts are incarcerated substantial distance from their family and friends and when the cost of phone services is substantially higher for incarcerees than among the general pubic. Also, it's known that better educated incarcerees are less likely to recidivate, but it's difficult and maybe impossible for many incarcerees to obtain education in prison.) # [[/Empower women and girls/]] [Cite research claiming that a primary restraint on population growth is empowering women and girls. Empowering women and girls is not just a matter of equity: It is also a means to reduce the threats of global warming, of increasing exposure to animal diseases and other problems that come with unrestrained population growth.] === Continuation === * [[/The evolving media literacy movement/]] to invite others to keep this book current with the evolving understanding of media literacy, how to encourage and promote it and the benefits of doing so. ==See also== * [[Wikibooks:Antiracist Activism for Teachers and Students/Points to Consider for Teaching Anti-racism/Media Literacy In Schools]] ==Notes== {{reflist}} ==Bibliography== * <!--Daron Acemoğlu and Simon Johnson (2023) Power and Progress-->{{cite Q|Q125292212}} * <!--Robin Andersen (2006) A century of media, a century of war-->{{cite Q|Q138795568}} * <!--Robin Andersen (2026-06-02) The Complicit Lens: US Media Coverage of Israel’s Genocide in Gaza-->{{cite Q|Q138796307}} * <!-- Matthew Baker and Dermot Murphy (2026-06-10) "Local News Shortage Leads to $1.1 Billion in Extra Borrowing Costs for Local Governments and Taxpayers"-->{{cite Q|Q141620048}} * <!--Perry Bacon Jr. (2022-10-17) "America Should Spend Billions to Revive Local News"-->{{cite Q|Q139594786}} * <!-- Joshua Benton (9 April 2019). "When local newspapers shrink, fewer people bother to run for mayor". Nieman Foundation for Journalism -->{{cite Q|Q63127216}} * <!--Stephen Bezruchka (2023) Inequality Kills Us All-->{{cite Q|Q136047815}} * <!--Stephen Bezruchka (2025) ''Born Sick in the USA''-->{{cite Q|Q138749292}} * <!--Renée DiResta (2024) Invisible Rulers: The People Who Turn Lies into Reality-->{{cite Q|Q135530439}} * <!--Robert Felix, Joshua A. Khavis, and Mikhail Pevzner (2024) "The effects of local newspaper closures on nonprofits’ executive compensation"-->{{cite Q|Q132730972}} * <!--Maxim Flößer (2024-03-06) "Keine Lokalzeitung -- mehr AfD", Kontext-->{{cite Q|Q125287792}} * <!--Pengjie Gao, Chang Lee, and Dermot Murphy (2018) "Financing Dies in Darkness? The Impact of Newspaper Closures on Public Finance"-->{{cite Q|Q55670016}} * <!--Spencer Graves (2024) "Wikipedia: The most democratic force on earth-->{{cite Q|Q137796922}} * <!--Spencer Graves and Bryan Bailey (2025) "We have to talk", blog at PeaceWorksKC.org-->{{cite Q|Q136126262}} * <!--Brad N. Greenwood (2026-06-09) "When Local Newspapers Die, Corruption Festers"-->{{cite Q|Q141620523}} * [[d:Q138038060|Dan Hind and Spencer Graves (2025) "Media Reform Coalition challenges anti-democratic media bias in the UK" on Wikiversity]]. * <!--Richard R. John (1995) Spreading the News: The American Postal System from Franklin to Morse-->{{cite Q|Q54641943}} * <!--Adam H. Johnson (2026-04-21) How to Sell a Genocide: The Media's Complicity in the Destruction of Gaza-->{{cite Q|Q140073447}} * <!--Louis Johnston and Samuel H. Williamson, "What Was the U.S. GDP Then?" MeasuringWorth, 2026-->{{cite Q|Q56881105}} * <!-- Min Kim, Derrald Stice, Han Stice, and Roger M. White (2021) "Stop the presses! Or wait, we might need them: Firm responses to local newspaper closures and layoffs"-->{{cite Q|Q132459373}} * <!-- Robert W. McChesney; John Nichols (2010). The Death and Life of American Journalism (Bold Type Books) -->{{cite Q|Q104888067}}. * <!-- Robert W. McChesney; John Nichols (2021). "The Local Journalism Initiative: a proposal to protect and extend democracy". Columbia Journalism Review, 30 November 2021 -->{{cite Q|Q109978060}} * <!-- Robert W. McChesney; John Nichols (2022), To Protect and Extend Democracy, Recreate Local News Media (PDF), FreePress.net (updated 25 January 2022) -->{{cite Q|Q109978337|access-date=2024-06-23}} * <!--Alfred W. McCoy (2003-05-01) The politics of heroin : CIA complicity in the global drug trade : Afghanistan, Southeast Asia, Central America, Colombia-->{{cite Q|Q141317509}} * <!--Joel Mokyr (2017) A Culture of Growth: The Origins of the Modern Economy (Graz Schumpeter Lectures; Princeton University Press)-->{{cite Q|Q136118590}} * <!--Neff and Pickard (2024) "Funding Democracy: Public Media and Democratic Health in 33 Countries"-->{{cite Q|Q131468289}} * [[d:Q131398359|Victor Pickard (2020) ''Democracy without journalism? : confronting the misinformation society'' (Oxford U. Pr.)]]. * <!-- Victor Pickard (2023-05-12) "Another Media System is Possible: Ripping Open the Overton Window, from Platforms to Public Broadcasting"-->{{cite Q|Q131398460}} * <!--Doug Samuelson (2025) Assessing Israel’s Approach in Gaza-->{{cite Q|Q138843324}} * [[d:Q138037937|Dean Starkman and Spencer Graves (2025) "Dean Starkman and the watchdog that didn't bark anglais" on Wikiversity]]. * <!--Mira Sucharov (2022) Do American Jews Really Know What 'Zionist' Means?-->{{cite Q|Q125903777}} * [[d:Q134715465|Nikki Usher and Sanghoon Kim-Leffingwell (2022) "How Loud Does the Watchdog Bark? A Reconsideration of Local Journalism, News Non-profits, and Political Corruption", ''SSRN Electronic Journal'']]. * [[d:Q61013892|Horacio Verbitsky (1997) ''Un mundo sin periodistas'' (in Spanish: A world without journalists; Editorial Sudamericana)]]. [[Category:Communication]] [[Category:Political science]] [[Category:Law]] [[Category:Psychology]] [[Category:Sociology]] [[Category:Education]] [[Category:Economics]] [[Category:Media Literacy and You]] [[Category:Freedom and abundance]] <!-- https://en.wikiversity.org/wiki/Category_Review --> kck2005m2v9rjud7h4z0of5mgwy7td1 0 329548 2835482 2833721 2026-10-02T09:12:29Z Athene241 3100061 /* Solve the problem */ 2835482 wikitext text/x-wiki {{mathematics}} '''Athena problem''' is an [[:w:List of unsolved problems in mathematics|unsolved problem]] in [[:w:Number theory|number theory]] and [[:w:Formal language theory|formal language theory]] and [[:w:Order theory|order theory]], this problem is named after the ancient Greek goddess [[:w:Athena|Athena]] (which is associated with [[:w:Wisdom|wisdom]]). Athena problem is: Give a [[:w:Natural number|natural number]] ''b'' > 1, find the [[:w:Set (mathematics)|set]] of the [[:w:Minimal element|minimal element]]s of the set of the "[[:w:Prime number|prime number]] [[:w:Greater than|>]] ''b''" [[:w:Numerical digit|digit]] [[:w:String (computer science)|string]]s in the [[:w:Positional numeral system|positional numeral system]] with [[:w:Radix|base]] ''b'' for the [[:w:Subsequence|subsequence]] [[:w:Partially ordered set|ordering]]. (A string ''x'' is a subsequence of another string ''y'', if ''x'' can be obtained from ''y'' by deleting zero or more of the [[:w:Character (computing)|character]]s in ''y''. For example, 514 is a subsequence of 352148, "string" is a subsequence of "meistersinger". In contrast, 758 is not a subsequence of 378259, "abc" is not a subsequence of "cbacacba", since the characters must be in the same order) (Unlike [[:w:Substring|substring]], subsequence is not required to occupy consecutive positions within the original sequences, e.g. the [[:w:Longest common subsequence|longest common subsequence problem]] is different from the [[:w:Longest common substring|longest common substring problem]]) Using [[:w:Formal language theory|formal language theory]] terminology, Athena problem is finding the [[:w:Set (mathematics)|set]] of the [[:w:Minimal element|minimal element]]s of the [[:w:Formal language|language]] of base-''b'' [[:w:Representation (mathematics)|representation]]s of the [[:w:Prime number|prime number]]s [[:w:Greater than|>]] ''b'' (which is a set of [[:w:String (computer science)|string]]s of [[:w:Symbol|symbol]]s over the [[:w:Alphabet (formal languages)|alphabet]] ''Σ''_''b'' := {0, 1, ..., ''b''−1}), under the subsequence ordering (i.e. the [[:w:Binary relation|binary relation]] "is a subsequence of", which is a [[:w:Partially ordered set|partial ordering]]), for a given natural number ''b'' > 1 (You can draw this partial ordering as a [[:w:Hasse diagram|Hasse diagram]] to find all [[:w:Minimal element|minimal element]]s), this set is called '''Athena set''', and the prime numbers in this set are called '''Athena primes'''. By [[:w:Higman's lemma|Higman's lemma]], there are no [[:w:Infinite set|infinite]] [[:w:Antichain|antichain]]s for the subsequence ordering (i.e. the subsequence ordering is always a [[:w:Well-quasi-ordering|well quasi order]]) (i.e. under the subsequence ordering (i.e. the [[:w:Binary relation|binary relation]] "is a subsequence of", which is a [[:w:Partially ordered set|partial ordering]]), every set of pairwise incomparable (i.e. not [[:w:Comparability|comparable]]) strings is finite), thus there must be only finitely many such minimal elements. In other words, the Athena set in every base ''b'' must be a [[:w:Finite set|finite set]], and every base ''b'' ≥ 2 has only finitely many Athena primes, e.g. in [[:w:Decimal|decimal]] (base ''b'' = 10), the Athena set has exactly 77 [[:w:Element of a set|element]]s (they are exactly the Athena primes in decimal (base ''b'' = 10)): {11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 227, 251, 257, 277, 281, 349, 409, 449, 499, 521, 557, 577, 587, 727, 757, 787, 821, 827, 857, 877, 881, 887, 991, 2087, 2221, 5051, 5081, 5501, 5581, 5801, 5851, 6469, 6949, 8501, 9001, 9049, 9221, 9551, 9649, 9851, 9949, 20021, 20201, 50207, 60649, 80051, 666649, 946669, 5200007, 22000001, 60000049, 66000049, 66600049, 80555551, 555555555551, 5000000000000000000000000000027}. Determining the set of the minimal elements of a arbitrary set of strings under the subsequence ordering is in general [[:w:List of unsolved problems in mathematics|unsolvable]], and can be difficult even when this set is relatively simple (such as the base ''b'' representations of the prime numbers > ''b'', whose set is exactly the Athena set in base ''b''). Although the set ''M''(''S'') of minimal strings is necessarily [[:w:Finite set|finite]], determining it explicitly for a given ''S'' can be a difficult computational problem. We use some [[:w:Number theory|numbertheoretic]] [[:w:Heuristic argument|heuristic]]s to [[:w:Computing|compute]] ''M''(''L''_''b'') (i.e. to compute the Athena set in base ''b''), where ''L''_''b'' is the [[:w:Formal language|language]] of [[:w:Radix|base]]-''b'' representations of the [[:w:Prime number|prime number]]s which are [[:w:Greater than|>]] ''b'', for 2 ≤ ''b'' ≤ 36. For bases 2 ≤ ''b'' ≤ 36, Athena problem is fully solved in bases ''b'' = 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 18, 20, 24, and also solved in bases ''b'' = 11, 13, 16, 22, 30 if [[:w:Probable prime|probable prime]]s are allowed. For the unsolved bases ''b'' = 17, 19, 21, 23, 25, 26, 27, 28, 29, 31, 32, 34, 35, 36, Athena problem is solved (if probable primes are allowed) except 771 [[:w:Indexed family|families]] of the form ''x''{''y''}''z'' (where ''x'' and ''z'' are strings (may be [[:w:Empty string|empty]]) of digits in base ''b'', ''y'' is a digit in base ''b'') = sequence {''xz'', ''xyz'', ''xyyz'', ''xyyyz'', ''xyyyyz'', ''xyyyyyz'', ...} (i.e. "''xy''⁺''z''" in [[:w:Regular expression|regular expression]]), all of these 771 families contain no primes > ''b'' or probable primes > ''b'' with length ≤ 100000. (The chance that an unproven probable prime in these sets is in fact composite is less than 10⁻²⁰⁰⁰, see https://t5k.org/notes/prp_prob.html) Below, family ''x''{''y''}''z'' (where ''x'' and ''z'' are strings (may be [[:w:Empty string|empty]]) of digits in base ''b'', ''y'' is a digit in base ''b'') means sequence {''xz'', ''xyz'', ''xyyz'', ''xyyyz'', ''xyyyyz'', ''xyyyyyz'', ...} (i.e. "''xy''⁺''z''" in [[:w:Regular expression|regular expression]]), where the members are expressed as base ''b'' strings, like the numbers in https://stdkmd.net/nrr/aaaab.htm, https://stdkmd.net/nrr/abbbb.htm, https://stdkmd.net/nrr/aaaba.htm, https://stdkmd.net/nrr/abaaa.htm, https://stdkmd.net/nrr/abbba.htm, https://stdkmd.net/nrr/abbbc.htm, e.g. 1{3} (in decimal) is the numbers in https://stdkmd.net/nrr/1/13333.htm#about_first, and {1}3 (in decimal) is the numbers in https://stdkmd.net/nrr/1/11113.htm#about_first, and 31{3} (in decimal) is the numbers in https://stdkmd.net/nrr/3/31333.htm#about_first, and {1}31 (in decimal) is the numbers in https://stdkmd.net/nrr/1/11131.htm#about_first, and 1{2}3 (in decimal) is the numbers in https://stdkmd.net/nrr/1/12223.htm#about_first, also, superscripts always means exponents, subscripts are always used to indicate repetitions of digits, e.g. 123₄567 = 123333567, all subscripts are written in decimal. == Solve the problem == To solve the Athena problem for a given base ''b'', we must [[:w:Computing|compute]] the elements up to families of the form ''x''{''y''}''z'' (where ''x'' and ''z'' are strings (may be empty) of digits in base ''b'', ''y'' is a digit in base ''b''), and find the smallest prime > ''b'' in all such families. We call families of the form ''x''{''y''}''z'' (where ''x'' and ''z'' are strings (may be empty) of digits in base ''b'', ''y'' is a digit in base ''b'') "linear" families, and we reduce these families by removing all trailing digits ''y'' from ''x'', and removing all leading digits ''y'' from ''z'', to make the families be easier, e.g. family 12333{3}33345 in base ''b'' is reduced to family 12{3}45 in base ''b'', since they are in fact the same family. Our [[:w:Algorithm|algorithm]] then proceeds as follows: * 1. ''M'' := {minimal primes in base ''b'' of length 2 or 3}, ''L'' := union of all ''x''{''Y''}''z'' (where ''x'' and ''z'' are strings (may be empty) of digits in base ''b'') such that ''x'' ≠ 0 and ''gcd''(''z'', ''b'') = 1 and ''Y'' is the set of digits ''y'' in base ''b'' such that ''xyz'' has no subsequence in ''M''. * 2. While ''L'' contains nonlinear families (families which are not linear families): Explore each family of ''L'', and update ''L''. Examine each family of ''L'' by: * 2.1. Let ''w'' be the shortest string in the family. If ''w'' has a subsequence in ''M'', then remove the family from ''L''. If ''w'' represents a prime, then add ''w'' to ''M'' and remove the family from ''L''. * 2.2. If possible, simplify the family. * 2.3. Using the techniques below (covering congruence, algebraic factorization, or combine of them), check if the family can be proven to only contain composites (only count the numbers > ''b''), and if so then remove the family from ''L''. * 3. Update ''L'', after each split examine the new families as in step 2. e.g. in decimal (base ''b'' = 10): ''M'' := {11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 227, 251, 257, 277, 281, 349, 409, 449, 499, 521, 557, 577, 587, 727, 757, 787, 821, 827, 857, 877, 881, 887, 991} ''L'' := {2{0,2}1, 2{0,8}7, 3{0,3,6,9}3, 3{0,3,6,9}9, 4{6}9, 5{0,5,8}1, 5{0,2}7, 6{0,3,6,9}3, 6{0,3,4,6,9}9, 7{0,7}7, 8{0,5}1, 8{0}7, 9{0,2,5,8}1, 9{0,3,6,9}3, 9{0,3,4,6,9}9} and since 2221 is prime, it follows that the family 2{0,2}1 splits into the families 2{0}1 and 2{0}2{0}1 and since the family 2{0}1 can be proven to contain no primes > base (since all numbers in this family are divisible by 3), it can be removed and since 20201 is prime, it follows that the family 2{0}2{0}1 splits into the families 2{0}21 and 22{0}1 221 and 2021 are composites, but 20021 is prime, thus add 20021 to ''L'' none of 221, 2201, 22001, 220001, 2200001 are primes, but 22000001 is prime, thus add 22000001 to ''L'' and since the family 3{0,3,6,9}3 can be proven to contain no primes > base (since all numbers in this family are divisible by 3), it can be removed etc. Since the number of possible (first digit,last digit) (also called (initial digit,final digit)) combos ([[:w:Ordered pair|ordered pair]]s) of a prime > ''b'' in base ''b'' is (''b''−1)×''[[:w:Euler's totient function|eulerphi]]''(''b'') (all digits except 0 can be the first digit of a prime > ''b'' in base ''b'' (thus ''b''−1 possible digits), but only the digits coprime to ''b'' can be the last digit of a prime > ''b'' in base ''b'' (thus ''eulerphi''(''b'') possible digits), and by the [[:w:Rule of product|rule of product]], there are (''b''−1)×''eulerphi''(''b'') choices of the (first digit,last digit) combo, also, both "numbers of Athena primes in base ''b''" and "length of the largest Athena prime in base ''b''" are [[:w:Asymptotic analysis|roughly]] ''[[:w:E (mathematical_constant)|e]]''^{''[[:w:Euler's constant|γ]]''×(''b''−1)×''[[:w:Euler's totient function|eulerphi]]''(*b*)}. Shrinking the family ''x''{''Y''}''z'' (where ''x'' and ''z'' are strings (may be empty) of digits in base ''b'', ''Y'' is a set of digits in base ''b'') * If ''y'' ∈ ''Y'' and the string ''xyyz'' represents a prime > ''b'' in base ''b'' (in this case, add this prime to the list) or has a subsequence which represents a prime > ''b'' in base ''b'', then ''x''{''Y''}''z'' can be replaced with ''x''{''Y'' \ ''y''}''z'' ∪ ''x''{''Y'' \ ''y''}''y''{''Y'' \ ''y''}''z''. * If ''y''₁ ∈ ''Y'' and ''y''₂ ∈ ''Y'' and ''y''₁ ≠ ''y''₂ and the string ''xy''₁''y''₂''z'' represents a prime > ''b'' in base ''b'' (in this case, add this prime to the list) or has a subsequence which represents a prime > ''b'' in base ''b'', then ''x''{''Y''}''z'' can be replaced with ''x''{''Y'' \ ''y''₁}{''Y'' \ ''y''₂}''z''. * If ''y''₁ ∈ ''Y'' and ''y''₂ ∈ ''Y'' and ''y''₁ ≠ ''y''₂ and both the strings ''xy''₁''y''₂''z'' and ''xy''₂''y''₁''z'' represent a prime > ''b'' in base ''b'' (in this case, add this prime to the list) or have a subsequence which represents a prime > ''b'' in base ''b'', then ''x''{''Y''}''z'' can be replaced with ''x''{''Y'' \ ''y''₁}''z'' ∪ ''x''{''Y'' \ ''y''₂}''z''. e.g. in decimal (base ''b'' = 10): * 2221 is a prime > 10, thus the family 2{0,2}1 splits into the two families 2{0}1 and 2{0}2{0}1. * 227 is a prime > 10, and it is a subsequence of 5227, thus the family 5{0,2}7 splits into the two families 5{0}7 and 5{0}2{0}7. * 449 is a prime > 10, and it is a subsequence of 6449, thus the family 6{0,3,4,6,9}9 splits into the two families 6{0,3,6,9}9 and 6{0,3,6,9}4{0,3,6,9}9. * Both 5051 and 5501 are primes > 10, thus the family 5{0,5}1 splits into the two families 5{0}1 and 5{5}1 = {5}1. * 8501 is a prime > 10, thus the family 8{0,5}1 splits into the family 8{0}{5}1. * 887 is a prime > 10, and it is a subsequence of 2887, also 2087 is a prime > 10, thus the family 2{0,8}7 splits into the two families 2{0}7 and 28{0}7. * 349 and 449 are primes > 10, and they are subsequences of 9349 and 9449, respectively, also 9049, 9649, 9949 are primes > 10, thus the family 9{0,3,4,6,9}9 splits into the two families 9{0,3,6,9}9 and 94{0,3,6,9}9. * 251, 281, 521, 821, 881 are primes > 10, and they are subsequences of 9251, 9281, 9521, 9821, 9881, respectively, also 9001, 9221, 9551, 9851 are primes > 10, thus the family 9{0,2,5,8}1 splits into the numbers {91, 901, 921, 951, 981, 9021, 9051, 9081, 9201, 9501, 9581, 9801, 90581, 95081, 95801}. If the methods we have discussed cannot be used to rule out or shrink ''x''{''Y''}''z'' where ''Y'' = {''y''₁, ''y''₂, ..., ''y''_''n''}, then we can replace ''x''{''Y''}''z'' by ''xy''₁{''Y''}''z'' ∪ ''xy''₂{''Y''}''z'' ∪ ... ∪ ''xy''_''n''{''Y''}''z'' and re-run the methods on this new [[:w:Formal language|language]]. If all remain families are linear families (i.e. of the form ''x''{''y''}''z'', where ''x'' and ''z'' are strings (may be empty) of digits in base ''b'', ''y'' is a digit in base ''b''), then we search the smallest (probable) primes in these families and add these primes to the list. e.g. in decimal (base ''b'' = 10): * The smallest prime in the family 5{0}27 is 5000000000000000000000000000027. * The smallest prime in the family {5}1 is 555555555551. * The smallest prime in the family 8{5}1 is 8555555555555555555551, but 8555555555555555555551 is not a minimal element since 555555555551 is a subsequence of 8555555555555555555551. There is no guarantee that the techniques discussed will ever terminate, but in practice they often do. They are able to determine the Athena set in base ''b'' for 2 ≤ ''b'' ≤ 16 and ''b'' = 18, 20, 22, 24, 30. The bases ''b'' = 17, 19, 21, 23, 25 ≤ ''b'' ≤ 29, 31 ≤ ''b'' ≤ 36 are solved with the exception of 771 families of the form ''x''{''y''}''z'' (where ''x'' and ''z'' are strings (may be empty) of digits in base ''b'', ''y'' is a digit in base ''b''). The following is a "[[:w:Semi-algorithm|semi-algorithm]]" that is guaranteed to solve the Athena problem for a given base ''b'', but it is not so easy to implement: # ''M'' = ''[[:w:Empty string|∅]]'' # while (''L'' ≠ ''∅'') do # choose ''x'', a shortest string in ''L'' # ''M'' := ''M'' ∪ {''x''} # ''L'' := ''L'' − ''sup''({''x''}) In practice, for arbitrary ''L'', we cannot feasibly carry out step 5. Instead, we work with ''L''&#39;, some regular overapproximation to ''L'', until we can show ''L''&#39; = ''∅'' (which implies ''L'' = ''∅''). In practice, ''L''&#39; is usually chosen to be a finite [[:w:Union (set theory)|union]] of sets of the form ''L''₁{''L''₂}''L''₃, where each of ''L''₁, ''L''₂, ''L''₃ is finite. In the case we consider in this project, we then have to determine whether such a family contains a prime or not. Thus, the [[:w:Time complexity|time complexity]] of the Athena problem in base ''b'' may be ''[[:w:Big O notation|O]]''(''[[:w:E (mathematical_constant)|e]]''^{''[[:w:Euler's constant|γ]]''×(''b''−1)×''[[:w:Euler's totient function|eulerphi]]''(*b*)}), and the [[:w:CPU time|CPU time]] of the Athena problem in base ''b'' may be longer than [[:w:Age of the universe|the age of the universe]] for bases ''b'' = 19, 23, 25, 27, 29, 31, 32, 33, 34, 35, also, Athena problem in bases ''b'' around 500 may be [[:w:NP-complete|NP-complete]] or [[:w:NP-hard|NP-hard]], or an [[:w:Undecidable problem|undecidable problem]], or an example of [[:w:Gödel's incompleteness theorems|Gödel's incompleteness theorems]] (like the [[:w:Continuum hypothesis|continuum hypothesis]] and the [[:w:Halting problem|halting problem]]). To solve the Athena problem (i.e. to compute the Athena set), we need to determine whether a given family contains a prime. In practice, if family ''x''{''Y''}''z'' (where ''x'' and ''z'' are strings (may be empty) of digits in base ''b'', ''Y'' is a set of digits in base ''b'') could not be ruled out as only containing composites and ''Y'' contains two or more digits, then a relatively small prime > ''b'' could always be found in this family. Intuitively, this is because there are a large number of small strings in such a family, and at least one is likely to be prime (e.g. there are 2^''n''−2 strings of length ''n'' in the family 1{3,7}9, and there are over a thousand strings of length 12 in the family 1{3,7}9, thus it is very impossible that these numbers are all composite). In the case ''Y'' contains only one digit, this family is of the form ''x''{''y''}''z'', and there is only a single string of each length > (the length of ''x'' + the length of ''z''), and it is not known if the following [[:w:Decision problem|decision problem]] is recursively solvable (just like [[:w:Sierpiński number|Sierpiński problem]] and [[:w:Riesel number|Riesel problem]], Sierpiński problem and Riesel problem can be generalized to other bases ''b'' (references: http://www.noprimeleftbehind.net/crus/Sierp-conjectures.htm, http://www.noprimeleftbehind.net/crus/Riesel-conjectures.htm, http://www.noprimeleftbehind.net/crus/Sierp-conjectures-powers2.htm, http://www.noprimeleftbehind.net/crus/Riesel-conjectures-powers2.htm, http://www.noprimeleftbehind.net/crus/Sierp-conjecture-reserves.htm, http://www.noprimeleftbehind.net/crus/Riesel-conjecture-reserves.htm), in fact, Athena problem base ''b'' covers the Sierpiński problem base ''b'' and the Riesel problem base ''b'' with ''k'' < ''b'', i.e. finding the smallest prime of the form ''k''×''b''^''n''+1 and ''k''×''b''^''n''−1 (or prove such prime does not exist) with ''k'' < ''b'' (specially, for bases ''b'' such that the conjectured smallest Sierpiński number or the conjectured smallest Riesel number is < ''b'', Athena problem base ''b'' covers the Sierpiński problem base ''b'' or the Riesel problem base ''b'', respectively), since the smallest prime of the form ''k''×''b''^''n''+1 and ''k''×''b''^''n''−1 (if exists) must be a minimal element in base ''b'', also, Athena problem base ''b'' covers finding the smallest prime of these forms in base ''b'' (or proving that such prime does not exist) (in fact, it is known that exactly what bases 2 ≤ ''b'' ≤ 1024 have the families listed in the table below as unsolved families, all of these families in all bases 2 ≤ ''b'' ≤ 1024 have been searched to length ≥ 10000 (for the family (''sqrt''(''b'')×''b''^''n''+1)/(''sqrt''(''b'')+1), bases 2 ≤ ''b'' ≤ 1048576, searched to length ≥ 5000)): (''b''^''n''−1)/(''b''−1) (for this form, ''n'' must be prime, and we want ''n'' ≥ 2) (references of this form: http://www.fermatquotient.com/PrimSerien/GenRepu.txt, https://web.archive.org/web/20021111141203/http://www.users.globalnet.co.uk/~aads/primes.html, http://www.primenumbers.net/Henri/us/MersFermus.htm, http://www.bitman.name/math/table/379, https://pzktupel.de/Primetables/TableRepunitGen.php, https://oeis.org/A084740, https://oeis.org/A084738, https://oeis.org/A128164, https://oeis.org/A285642; or for prime bases ''b'': https://oeis.org/A065854, https://oeis.org/A279068), ''b''^''n''+1 (for this form, ''n'' must be power of 2, and we want ''n'' ≥ 1) (references of this form: http://jeppesn.dk/generalized-fermat.html, http://www.noprimeleftbehind.net/crus/GFN-primes.htm, https://web.archive.org/web/20231002190634/http://yves.gallot.pagesperso-orange.fr/primes/index.html, https://pzktupel.de/Primetables/TableFermatGFBB.php, https://oeis.org/A079706, https://oeis.org/A084712, https://oeis.org/A228101), (''b''^''n''+1)/2 (for odd ''b'') (for this form, ''n'' must be power of 2, and we want ''n'' ≥ 2) (reference of this form: http://www.fermatquotient.com/PrimSerien/GenFermOdd.txt), (''sqrt''(''b'')×''b''^''n''+1)/(''sqrt''(''b'')+1) (for square ''b'') (for this form, 2×''n''+1 must be prime, and we want ''n'' ≥ 2) (references of this form: http://www.fermatquotient.com/PrimSerien/GenRepuP.txt, http://www.primenumbers.net/Henri/us/MersFermus.htm, http://www.bitman.name/math/table/488, https://pzktupel.de/Primetables/TableWagstaffGen.php, https://oeis.org/A084742, https://oeis.org/A084741; or for bases ''b'' with ''sqrt''(''b'') prime: https://oeis.org/A065507), ((''b''−2)×''b''^''n''+1)/(''b''−1) (''n'' ≥ 2) (reference of this form: https://oeis.org/A243404), 2×''b''^''n''+1 (''n'' ≥ 1) (references of this form: https://www.mersenneforum.org/showthread.php?t=6918, https://www.mersenneforum.org/showthread.php?t=19725, https://oeis.org/A119624), 2×''b''^''n''−1 (''n'' ≥ 1) (references of this form: https://www.mersenneforum.org/showthread.php?t=24576, https://www.mersenneforum.org/attachment.php?attachmentid=20976&d=1567314217, https://oeis.org/A119591), ''b''^''n''+2 (''n'' ≥ 1) (references of this form: https://oeis.org/A138066, https://oeis.org/A084713, https://oeis.org/A138067), ''b''^''n''−2 (''n'' ≥ 2) (references of this form: https://www.primepuzzles.net/puzzles/puzz_887.htm, https://oeis.org/A250200, https://oeis.org/A255707, https://oeis.org/A084714; or for prime bases ''b'': https://oeis.org/A292201), (''b''−1)×''b''^''n''+1 (''n'' ≥ 1) (references of this form: http://www.noprimeleftbehind.net/Williams-primes-MP.htm, http://www.bitman.name/math/table/477, https://pzktupel.de/Primetables/TableWilliams2.php, https://oeis.org/A305531; or for prime bases ''b'': https://oeis.org/A087139), (''b''−1)×''b''^''n''−1 (''n'' ≥ 1) (references of this form: https://harvey563.tripod.com/wills.txt, http://www.noprimeleftbehind.net/Williams-primes-MM.htm, http://www.bitman.name/math/table/484, https://pzktupel.de/Primetables/TableWilliams1.php; or for prime bases ''b'': https://oeis.org/A122396), ''b''^''n''+(''b''−1) (''n'' ≥ 1) (references of this form: http://www.bitman.name/math/table/795, https://pzktupel.de/Primetables/TableWilliams6.php, https://oeis.org/A076845, https://oeis.org/A076846, https://oeis.org/A078178, https://oeis.org/A078179), ''b''^''n''−(''b''−1) (''n'' ≥ 2) (references of this form: http://www.bitman.name/math/table/792, https://pzktupel.de/Primetables/TableWilliams5.php, https://oeis.org/A113516, https://oeis.org/A343589; or for prime bases ''b'': https://cs.uwaterloo.ca/journals/JIS/VOL3/mccranie.html, http://www.bitman.name/math/table/435)): '''Problem: Given strings ''x'', ''z'' (may be empty), a digit ''y'', and a base ''b'' (''x'' does not [[:w:Leading zero|start with the digit 0]], ''z'' ends with a digit which [[:w:Coprime integers|coprime]] to ''b'', ''y'' is not 0 if ''x'' is empty, ''y'' is coprime to ''b'' if ''z'' is empty), does there exist a prime number whose base-''b'' expansion is of the form ''xy''_''n''''z'' for some ''n'' ≥ 0?''' An [[:w:Algorithm|algorithm]] to solve this problem, for example, would allow us to decide if there are any additional [[:w:Fermat prime|Fermat prime]]s other than the known ones (corresponding to ''n'' = 0, 1, 2, 3, 4). To see this, take ''b'' = 2, ''x'' = 1, ''y'' = 0, and ''z'' = 0₁₆1. Since if 2^''n''+1 is prime then ''n'' must be a [[:w:Power of 2|power of two]], a prime of the form ''xy''_''n''''z'' in base ''b'' must be a new Fermat prime. Besides, it would allow us to decide if there are infinitely many [[:w:Mersenne prime|Mersenne prime]]s (of the form 2^''p''−1 with prime ''p''). To see this, take ''b'' = 2, ''x'' = ''𝜆'' (the [[:w:Empty string|empty string]]), ''y'' = 1, and ''z'' = 1_''n''+1, where ''n'' is the exponent of the Mersenne prime which we want to know whether it is the largest Mersenne prime or not. Since if 2^''n''−1 is prime then ''n'' must be a [[:w:Prime number|prime]], a prime of the form ''xy''_''n''''z'' in base ''b'' must be a new Mersenne prime. Also, it would allow us to decide whether 78557 is the smallest [[:w:Sierpinski number|Sierpinski number]] (i.e. odd numbers ''k'' such that ''k''×2^''n''+1 is composite for all ''n'' ≥ 1) and whether 509203 is the smallest [[:w:Riesel number|Riesel number]] (i.e. odd numbers ''k'' such that ''k''×2^*n*−1 is composite for all ''n'' ≥ 1), etc. '''Conjecture (this conjecture is very important for the Athena problem): If family ''xy''_''n''''z'' (with fixed strings ''x'', ''z'' (may be empty), fixed digit ''y'', and variable ''n'') in base ''b'' (with fixed ''b'' ≥ 2) (''x'' does not start with the digit 0, ''z'' ends with a digit which coprime to ''b'', ''y'' is not 0 if ''x'' is empty, ''y'' is coprime to ''b'' if ''z'' is empty) cannot be proven to only contain composites or only contain finitely many primes (by covering congruence, algebraic factorization, or combine of them), then family ''xy''_''n''''z'' in base ''b'' contains infinitely many primes (this is equivalent to: If form (''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1) (with fixed integers ''a'' ≥ 1, ''b'' ≥ 2, ''c'' ≠ 0 (with ''gcd''(''a'',''c'') = 1 and ''gcd''(''b'',''c'') = 1), and variable ''n'') cannot be proven to only contain composites or only contain finitely many primes (by covering congruence, algebraic factorization, or combine of them), then form (''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1) contains infinitely many primes).''' (in fact, this conjecture is equivalent to the conjecture (to prove this, by change the base (''b'') to a power of ''b'' which is larger than the largest prime in a given family (in base ''b'') which only contains finitely many primes): If family ''xy''_''n''''z'' (with fixed strings ''x'', ''z'' (may be empty), fixed digit ''y'', and variable ''n'') in base ''b'' (with fixed ''b'' ≥ 2) (''x'' does not start with the digit 0, ''z'' ends with a digit which coprime to ''b'', ''y'' is not 0 if ''x'' is empty, ''y'' is coprime to ''b'' if ''z'' is empty) cannot be proven to only contain composites (by covering congruence, algebraic factorization, or combine of them), then family ''xy''_''n''''z'' in base ''b'' contains at least one prime (this is equivalent to: If form (''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1) (with fixed integers ''a'' ≥ 1, ''b'' ≥ 2, ''c'' ≠ 0 (with ''gcd''(''a'',''c'') = 1 and ''gcd''(''b'',''c'') = 1), and variable ''n'') cannot be proven to only contain composites (by covering congruence, algebraic factorization, or combine of them), then form (''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1) contains at least one prime), like the [[:w:Bunyakovsky conjecture|Bunyakovsky conjecture]] and the [[:w:Dickson's conjecture|Dickson's conjecture]] and the [[:w:Schinzel's hypothesis H|Schinzel's hypothesis ''H'']], if such ''n'' always exists, then there must be always infinitely many such ''n'', to prove this, add another polynomial for the cases of the Dickson's conjecture and the Schinzel's hypothesis ''H'', also, change the polynomial (e.g. change ''n'' to ''r''×''n'' or ''n''^''r'' for all integers ''r'' > 1) for the cases of the Bunyakovsky conjecture and the Schinzel's hypothesis ''H'') Some families can be ruled out to contain no prime > ''b'' by [[:w:Covering set|covering congruence]], [[:w:Factorization of polynomials|algebraic factorization]] (e.g. [[:w:Difference of two squares|difference of two squares]], [[:w:Sum of two cubes|sum of two cubes]], [[:w:Sophie Germain's identity|Sophie Germain's identity of ''x''⁴+4×''y''⁴]]), or combine of them, e.g. * The base 9 family 2{7}: Always divisible by 2 or 5 * The base 11 family 2{5}: Always divisible by 2 or 3 * The base 14 family B{0}1: Always divisible by 3 or 5 * The base 13 family 95{0}3: Always divisible by 5, 7, or 17 * The base 16 family {4}D: Always divisible by 3, 7, or 13 * The base 16 family {8}F: Always divisible by 3, 7, or 13 * The base 21 family {7}D: Always divisible by 2, 13, or 17 * The base 23 family {D}GA: Always divisible by 2, 5, 7, 37, or 79 * The base 9 family {1}: Can be written as (9^''n''−1)/8 and can be factored as (3^''n''−1) × (3^''n''+1) / 8 * The base 8 family 1{0}1: Can be written as 8^''n''+1 and can be factored as (2^''n''+1) × (4^''n''−2^''n''+1) * The base 9 family 3{8}: Can be written as 4×9^''n''−1 and can be factored as (2×3^''n''−1) × (2×3^''n''+1) * The base 16 family 1{5}: Can be written as (4×16^''n''−1)/3 and can be factored as (2×3^''n''−1) × (2×3^''n''+1) / 3 * The base 16 family {4}1: Can be written as (4×16^''n''−49)/15 and can be factored as (2×3^''n''−7) × (2×3^''n''+7) / 15 * The base 27 family 7{Q}: Can be written as 8×27^''n''−1 and can be factored as (2×3^''n''−1) × (4×9^''n''+2×3^''n''+1) * The base 27 family 9{G}: Can be written as (125×27^''n''−8)/13 and can be factored as (5×3^''n''−2) × (25×9^''n''+10×3^''n''+4) * The base 16 family {C}D: Can be written as (4×16^''n''+1)/5 and can be factored as (2×4^''n''−2×2^''n''+1) × (2×4^''n''+2×2^''n''+1) / 5 * The base 14 family 8{D}: Can be written as 9×14^''n''−1, it is divisible by 5 if ''n'' is odd and can be factored as (3×14^''n''/2−1) × (3×14^''n''/2+1) if ''n'' is even * The base 12 family {B}9B: Can be written as 12^''n''−25, it is divisible by 13 if ''n'' is odd and can be factored as (12^''n''/2−5) × (12^''n''/2+5) if ''n'' is even * The base 14 family {D}5: Can be written as 14^''n''−9, it is divisible by 5 if ''n'' is odd and can be factored as (14^''n''/2−3) × (14^''n''/2+3) if ''n'' is even * The base 17 family 1{9}: Can be written as (25×17^''n''−9)/16, it is divisible by 2 if ''n'' is odd and can be factored as (5×17^''n''/2−3) × (5×17^''n''/2+3) / 16 if ''n'' is even * The base 17 family 7{9}: Can be written as (121×17^''n''−9)/16, it is divisible by 2 if ''n'' is odd and can be factored as (11×17^''n''/2−3) × (11×17^''n''/2+3) / 16 if ''n'' is even * The base 24 family 3{N}: Can be written as 4×24^''n''−1, it is divisible by 5 if ''n'' is odd and can be factored as (2×24^''n''/2−1) × (2×24^''n''/2+1) if ''n'' is even * The base 24 family 5{N}: Can be written as 6×24^''n''−1, it is divisible by 5 if ''n'' is even and can be factored as (12×24^{(''n''−1)/2}−1) × (12×24^{(''n''−1)/2}+1) if ''n'' is odd * The base 33 family F{W}: Can be written as 16×33^''n''−1, it is divisible by 17 if ''n'' is odd and can be factored as (4×33^''n''/2−1) × (4×33^''n''/2+1) if ''n'' is even If the conjecture above is true, then the [[:w:Sierpiński number|Sierpiński conjecture]] and [[:w:Riesel number|Riesel conjecture]] are also true, and the [https://www.mersenneforum.org/showthread.php?t=10761 dual Sierpiński conjecture] and the [https://www.mersenneforum.org/showthread.php?t=6545 dual Riesel conjecture] are also true, and the [http://www.noprimeleftbehind.net/crus/Sierp-conjectures.htm Sierpiński conjectures] and the [http://www.noprimeleftbehind.net/crus/Riesel-conjectures.htm Riesel conjectures] in all bases ''b'' are also true, and the [http://www.noprimeleftbehind.net/crus/SNOB-Sierp-conjectures.htm real Sierpiński conjectures] and the [http://www.noprimeleftbehind.net/crus/Real-Riesel-conjectures.htm real Riesel conjectures] are also true, also, if the Athena conjecture is true, then there are infinitely many primes of these forms for fixed bases ''b'' ≥ 2 and variable exponents ''n'': * (''b''^''n''−1)/(''b''−1) for all bases ''b'' which are not [[:w:Perfect power|perfect power]]s (for this form, ''n'' must be prime) (references of this form: http://www.fermatquotient.com/PrimSerien/GenRepu.txt, https://web.archive.org/web/20021111141203/http://www.users.globalnet.co.uk/~aads/primes.html, http://www.primenumbers.net/Henri/us/MersFermus.htm, http://www.bitman.name/math/table/379, https://pzktupel.de/Primetables/TableRepunitGen.php, https://oeis.org/A084740, https://oeis.org/A084738, https://oeis.org/A128164, https://oeis.org/A285642; or for prime bases ''b'': https://oeis.org/A065854, https://oeis.org/A279068) * ''b''^''n''+1 for all even bases ''b'' which are not of the form ''m''^''r'' with odd ''r'' > 1 (for this form, ''n'' must be power of 2) (references of this form: http://jeppesn.dk/generalized-fermat.html, http://www.noprimeleftbehind.net/crus/GFN-primes.htm, https://web.archive.org/web/20231002190634/http://yves.gallot.pagesperso-orange.fr/primes/index.html, https://pzktupel.de/Primetables/TableFermatGFBB.php, https://oeis.org/A079706, https://oeis.org/A084712, https://oeis.org/A228101) * (''b''^''n''+1)/2 for all odd bases ''b'' which are not of the form ''m''^''r'' with odd ''r'' > 1 (for this form, ''n'' must be power of 2) (reference of this form: http://www.fermatquotient.com/PrimSerien/GenFermOdd.txt) * (''b''^''n''+1)/(''b''+1) for all bases ''b'' which are neither of the form ''m''^''r'' with odd ''r'' > 1 nor of the form 4×''m''⁴ (for this form, ''n'' must be prime) (references of this form: http://www.fermatquotient.com/PrimSerien/GenRepuP.txt, http://www.primenumbers.net/Henri/us/MersFermus.htm, http://www.bitman.name/math/table/488, https://pzktupel.de/Primetables/TableWagstaffGen.php, https://oeis.org/A084742, https://oeis.org/A084741; or for prime bases ''b'': https://oeis.org/A065507) * ((''b''−2)×''b''^''n''+1)/(''b''−1) for all bases ''b'' > 2 (reference of this form: https://oeis.org/A243404) * 2×''b''^''n''+1 for all bases ''b'' < 201446503145165177, not == 1 mod 3 (references of this form: https://www.mersenneforum.org/showthread.php?t=6918, https://www.mersenneforum.org/showthread.php?t=19725, https://oeis.org/A119624) * 2×''b''^''n''−1 for all bases ''b'' (references of this form: https://www.mersenneforum.org/showthread.php?t=24576, https://www.mersenneforum.org/attachment.php?attachmentid=20976&d=1567314217, https://oeis.org/A119591) * 3×''b''^''n''+1 for all even bases ''b'' * 3×''b''^''n''−1 for all even bases ''b'' * 4×''b''^''n''+1 for all bases ''b'' not == 1 mod 5, not == 14 mod 15, not [[:w:Fourth power|fourth power]]s * 4×''b''^''n''−1 for all bases ''b'' not == 1 mod 3, not == 4 mod 5, not [[:w:Square number|square]]s * 5×''b''^''n''+1 for all even bases ''b'' < 140324348, not == 1 mod 3 * 5×''b''^''n''−1 for all even bases ''b'' * 6×''b''^''n''+1 for all bases ''b'' not == 1 mod 7, not == 34 mod 35 * 6×''b''^''n''−1 for all bases ''b'' not == 1 mod 5, not == 34 mod 35, not of the form 6×''m''² with ''m'' == 2, 3 mod 5 * 7×''b''^''n''+1 for all even bases ''b'' * 7×''b''^''n''−1 for all even bases ''b'' < 9162668342, not == 1 mod 3 * 8×''b''^''n''+1 for all bases ''b'' not == 1 mod 3, not == 20 mod 21, not == 47, 83 mod 195, not == 467, 4343, 9887, 25448, 35978, 41522, 42647, 57083 mod 73815, not == 722, 83813, 206672, 239432, 322523, 1283843, 1519577, 1522553 mod 1551615, ..., not [[:w:Cube (algebra)|cube]]s * 8×''b''^''n''−1 for all bases ''b'' not == 1 mod 7, not == 20 mod 21, not == 83, 307 mod 455, not == 1266, 13593, 27292, 46353 mod 63973, ..., not [[:w:Cube (algebra)|cube]]s * 9×''b''^''n''+1 for all even bases ''b'' < 177744, not == 1 mod 5 * 9×''b''^''n''−1 for all even bases ''b'' not == 4 mod 5, not [[:w:Square number|square]]s * 10×''b''^''n''+1 for all bases ''b'' not == 1 mod 11, not == 32 mod 33 (references of this form: https://oeis.org/A088782) * 10×''b''^''n''−1 for all bases ''b'' not == 1 mod 3, not == 32 mod 33 * 11×''b''^''n''+1 for all even bases ''b'' not == 1 mod 3, not == 14 mod 15 * 11×''b''^''n''−1 for all even bases ''b'' not == 1 mod 5, not == 14 mod 15, not of the form 11×''m''² with ''m'' == 2, 3 mod 5 * 12×''b''^''n''+1 for all bases ''b'' not == 1 mod 13, not == 142 mod 143, not == 562, 828, 900, 1166 mod 1729, not == 597, 1143 mod 1885, not == 296, 901, 1759, 3090, 4553, 5521, 5807, 6016, 6984, 7094, 7270, 7380, 7479, 8447, 8557, 8733, 8843, 9910, 10020, 10196, 10306, 11483, 11769, 12737, 14200, 15531, 16994, 18457 mod 19019, not == 563, 1433, 13212, 15097, 19848, 20718, 32497, 34382, 39133, 51782, 53667, 58418, 58452, 60337, 60883, 71067, 72952, 77737, 79622, 80168, 94267, 97022, 98583, 98907, 113552, 116307, 117868, 118192, 131967, 132513, 132837, 134398, 151252, 151798, 152122, 153683, 170537, 171083, 172968, 177753, 179638, 189822, 190368, 192253, 192287, 197038, 198923, 211572, 213568, 216323, 218208, 229987, 232853, 235608, 237493, 249272 mod 250705, ... * 12×''b''^''n''−1 for all bases ''b'' not == 1 mod 11, not == 142 mod 143, not == 307, 1143 mod 1595, not == 901, 6016, 7479, 18457 mod 19019, ... * ''b''^''n''+2 for all odd bases ''b'' < 201446503145165177, not == 1 mod 3 (references of this form: https://oeis.org/A138066, https://oeis.org/A084713, https://oeis.org/A138067) * ''b''^''n''−2 for all odd bases ''b'' (references of this form: https://www.primepuzzles.net/puzzles/puzz_887.htm, https://oeis.org/A250200, https://oeis.org/A255707, https://oeis.org/A084714; or for prime bases ''b'': https://oeis.org/A292201) * ''b''^''n''+3 for all even bases ''b'' not divisible by 3 * ''b''^''n''−3 for all even bases ''b'' not divisible by 3 * ''b''^''n''+4 for all odd bases ''b'' not == 1 mod 5, not == 14 mod 15, not [[:w:Fourth power|fourth power]]s * ''b''^''n''−4 for all odd bases ''b'' not == 1 mod 3, not == 4 mod 5, not [[:w:Square number|square]]s * (''b''−1)×''b''^''n''+1 for all bases ''b'' (references of this form: http://www.noprimeleftbehind.net/Williams-primes-MP.htm, http://www.bitman.name/math/table/477, https://pzktupel.de/Primetables/TableWilliams2.php, https://oeis.org/A305531; or for prime bases ''b'': https://oeis.org/A087139) * (''b''−1)×''b''^''n''−1 for all bases ''b'' (references of this form: https://harvey563.tripod.com/wills.txt, http://www.noprimeleftbehind.net/Williams-primes-MM.htm, http://www.bitman.name/math/table/484, https://pzktupel.de/Primetables/TableWilliams1.php; or for prime bases ''b'': https://oeis.org/A122396) * (''b''+1)×''b''^''n''+1 for all bases ''b'' not == 1 mod 3 (references of this form: http://www.noprimeleftbehind.net/Williams-primes-PP.htm, http://www.bitman.name/math/table/474, https://pzktupel.de/Primetables/TableWilliams4.php) * (''b''+1)×''b''^''n''−1 for all bases ''b'' (references of this form: http://www.noprimeleftbehind.net/Williams-primes-PM.htm, http://www.bitman.name/math/table/471, https://pzktupel.de/Primetables/TableWilliams3.php) * ''b''^''n''+(''b''−1) for all bases ''b'' (references of this form: http://www.bitman.name/math/table/795, https://pzktupel.de/Primetables/TableWilliams6.php, https://oeis.org/A076845, https://oeis.org/A076846, https://oeis.org/A078178, https://oeis.org/A078179) * ''b''^''n''−(''b''−1) for all bases ''b'' (references of this form: http://www.bitman.name/math/table/792, https://pzktupel.de/Primetables/TableWilliams5.php, https://oeis.org/A113516, https://oeis.org/A343589; or for prime bases ''b'': https://cs.uwaterloo.ca/journals/JIS/VOL3/mccranie.html, http://www.bitman.name/math/table/435) * ''b''^''n''+(''b''+1) for all bases ''b'' not == 1 mod 3 (references of this form: http://www.bitman.name/math/table/801, https://pzktupel.de/Primetables/TableWilliams8.php, https://oeis.org/A346149, https://oeis.org/A346154) * ''b''^''n''−(''b''+1) for all bases ''b'' (references of this form: http://www.bitman.name/math/table/798, https://pzktupel.de/Primetables/TableWilliams7.php, https://oeis.org/A178250) By the [[:w:Prime number theorem|prime number theorem]], the [[:w:Probability|chance]] that a [[:w:Random number|random]] ''n''-digit base ''b'' number is prime is [[:w:Asymptotic analysis|approximately]] 1/''n'' (more accurately, the chance is approximately 1/(''n''×''ln''(''b'')), where ''ln'' is the [[:w:Natural logarithm|natural logarithm]]). If one conjectures the numbers ''x''{''y''}''z'' behave similarly (i.e. the numbers ''x''{''y''}''z'' is a [[:w:Pseudorandomness|pseudorandom sequence]]) you would expect [[:w:Harmonic_series (mathematics)|1/1 + 1/2 + 1/3 + 1/4 + ... = ∞]] primes of the form ''x''{''y''}''z'' (of course, this does not always happen, since some ''x''{''y''}''z'' families can be ruled out to contain no prime > ''b'' (by covering congruence, algebraic factorization, or combine of them), but it is at least a reasonable conjecture in the absence of evidence to the contrary. Hence, the [[:w:Heuristic argument|heuristic argument]] suggests there are always infinitely many primes in family ''x''{''y''}''z'' (where ''x'' and ''z'' are strings (may be empty) of digits in base ''b'', ''y'' is a digit in base ''b'') if it cannot be ruled out to contain no prime or only contain finitely many primes, by covering congruence, algebraic factorization, or combine of them. However, some families ''x''{''y''}''z'' could not be proven to contain no primes > ''b'' (by covering congruence, algebraic factorization, or combine of them) but no primes > ''b'' could be found in the family, even after searching through numbers with over 100000 digits. In such a case, the only way to proceed is to [[:w:Primality test|test the primality]] of larger and larger numbers of such form and hope a prime is eventually discovered. e.g. the smallest (probable) prime in the family A{3}A in base ''b'' = 13 is A3₅₉₂₁₉₇A, its algebraic form is (41×13⁵⁹²¹⁹⁸+27)/4, when written in decimal contains 659677 digits (it is only probable prime, i.e. not definitely prime, since technically, probable primality tests were used to show this (which have a ''very'' small chance of making an error, see https://t5k.org/notes/prp_prob.html) because all known primality tests run far too slowly to run on numbers of this size unless either [https://t5k.org/prove/prove3_1.html ''N''−1] or [https://t5k.org/prove/prove3_2.html ''N''+1] (or both) can be ≥ 1/3 factored). The numbers in family ''x''{''y''}''z'' (where ''x'' and ''z'' are strings (may be empty) of digits in base ''b'', ''y'' is a digit in base ''b'') are of the form (''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1) for some fixed ''a'', ''b'', ''c'' such that ''a'' ≥ 1, ''b'' ≥ 2 (''b'' is the base), ''c'' ≠ 0, ''gcd''(''a'',''c'') = 1, ''gcd''(''b'',''c'') = 1. Except in the [[:w:Special case|special case]] ''c'' = ±1 and ''gcd''(''a''+''c'',''b''−1) = 1 (the only case which [https://t5k.org/prove/prove3_1.html ''N''−1] or [https://t5k.org/prove/prove3_2.html ''N''+1] is [[:w:Triviality (mathematics)|trivially]] fully factored), when ''n'' is large the known [[:w:Primality test|primality test]]s for such a number are too inefficient to run (since they are [https://t5k.org/glossary/xpage/OrdinaryPrime.html ordinary primes]). In this case one must resort to a [[:w:Probabilistic algorithm|probable]] primality test such as a [[:w:Miller–Rabin primality test|Miller–Rabin primality test]] or a [[:w:Baillie–PSW primality test|Baillie–PSW primality test]], unless a divisor of the number can be found. Since we are testing many numbers in an [[:w:Exponential growth|exponential sequence]], it is possible to use a sieving process to find divisors rather than using [[:w:Trial division|trial division]]. To do this, we made use of Geoffrey Reynolds' ''srsieve'' software (download: https://pzktupel.de/Software/srsieve_1.1.4.7z). This program uses the [[:w:Baby-step giant-step|baby-step giant-step]] [[:w:Algorithm|algorithm]] to find all primes ''p'' which divide ''a''×''b''^''n''+''c'' where ''p'' and ''n'' lie in a [[:w:Interval_(mathematics)|specified range]]. Since this program cannot handle the general case (''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1) when ''gcd''(''a''+''c'',''b''−1) > 1 we only used it to sieve the sequence ''a''×''b''^''n''+''c'' for primes ''p'' not dividing ''gcd''(''a''+''c'',''b''−1), and initialized the list of candidates to not include ''n'' for which there is some prime ''p'' dividing ''gcd''(''a''+''c'',''b''−1) for which ''p'' dividing (''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1). The program had to be modified slightly to remove a check which would prevent it from running in the case when ''a'', ''b'', and ''c'' were all odd (since then 2 divides ''a''×''b''^''n''+''c'', but 2 may not divide (''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1)). Once the numbers with small divisors had been removed, it remained to test the remaining numbers using a probable primality test. For this we used the software ''LLR'' by Jean Penné. (download: http://jpenne.free.fr/index2.html). Although undocumented, it is possible to run this program on numbers of the form (''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1) when ''gcd''(''a''+''c'',''b''−1) > 1, so this program required no modifications. A script was also written which allowed one to run ''srsieve'' while ''LLR'' was testing the remaining candidates, so that when a divisor was found by srsieve on a number which had not yet been tested by ''LLR'' it would be removed from the list of candidates. For the primes < 10²⁵⁰⁰⁰ for the "easy" bases (bases ''b'' with ≤ 150 primes > 10²⁹⁹ (base ''b'' = 26 has 83 known primes > 10²⁹⁹ and 3 unsolved families, base ''b'' = 36 has 75 known primes > 10²⁹⁹ and 4 unsolved families, base ''b'' = 17 has 99 known primes > 10²⁹⁹ and 18 unsolved families, base ''b'' = 21 has 80 known primes > 10²⁹⁹ and 12 unsolved families, base ''b'' = 19 has 201 known primes > 10²⁹⁹ and 23 unsolved families), i.e. bases *b* = 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 26, 28, 30, 36), we employed ''CM'' by Andreas Enge (download: https://www.multiprecision.org/cm/download.html), an elliptic curve primality proving implementation. Currently, the final goal of the Athena problem project is finding the Athena set (i.e. finding all Athena primes) and proving that this set is exactly the Athena set (i.e. proving that these are all Athena primes (including the primality proving for the probable primes)) in all bases 2 ≤ ''b'' ≤ 36, i.e. solving all families in all bases 2 ≤ ''b'' ≤ 36. Solving all (unsolved) families in all bases 2 ≤ ''b'' ≤ 36 (and proving the primality of all probable primes in the sets of all bases 2 ≤ ''b'' ≤ 36) is not possible but we aim to solve many of them (and proving the primality of many of them), at least find a ''probable'' prime for many of them (since the smallest prime in a family may be too large (> 10²⁵⁰⁰⁰) to be proved primality, unless its ''N''−1 or/and ''N''+1 can be ≥ 25% factored). == Data == These are the results of the Athena problem in bases 2 ≤ ''b'' ≤ 36 (we stop at base 36 since this base is the maximum base for which it is possible to write the numbers with the [[:w:Symbol|symbol]]s 0, 1, 2, ..., 9 and A, B, C, ..., Z (i.e. the 10 [[:w:Arabic numerals|Arabic numerals]] and the 26 [[:w:Latin script|Latin letters]]): (some large Athena primes are only probable primes, i.e. not definitely primes, since they are too large to be [[:w:Elliptic curve primality|ECPP proved]] and [[:w:Pocklington primality test#Extensions and variants|neither ''N''−1 nor ''N''+1 can be ≥ 1/3 factored]] (Brillhart-Lehmer-Selfridge primality test), all of them pass the [[:w:Baillie–PSW primality test|Baillie–PSW primality test]] and the [[:w:Strong pseudoprime|strong primality test]] (i.e. the [[:w:Miller–Rabin primality test|Miller–Rabin primality test]]) with all prime bases ''p'' ≤ 61, however, all Athena primes < 10²⁵⁰⁰⁰ for bases ''b'' = 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 20, 22, 24, 26, 28, 30, 36 are definitely primes, most of them > 10²⁹⁹ are proven primes with [[:w:Elliptic curve primality|ECPP proving]], others > 10²⁹⁹ are proven primes with [[:w:Pocklington primality test#Extensions and variants|''N''−1 or ''N''+1 proving]]) The Athena primes > 10²⁹⁹ in bases ''b'' = 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 26, 28, 30, 36 which are proven primes with ''N''−1 or ''N''+1 proving includes the Athena primes whose ''N''−1 or ''N''+1 is trivially fully factored: * the 3176th Athena prime in base 13, 81010₄₁₅1, which equals 17746×13⁴¹⁶+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000003590431555, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000003590431556&open=ecm * the 3177th Athena prime in base 13, 8110₄₃₅1, which equals 1366×13⁴³⁶+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000002373259109, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000002373259124&open=ecm * the 3188th Athena prime in base 13, 930₁₅₅₁1, which equals 120×13¹⁵⁵²+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000765961452, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000765961453&open=ecm * the 3191st Athena prime in base 13, 390₆₂₆₆1, which equals 48×13⁶²⁶⁷+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000765961441, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000765961451&open=ecm * the 649th Athena prime in base 14, 34D₇₀₈, which equals 47×14⁷⁰⁸−1, ''N''+1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000001540144903, for the factorization of ''N''+1 in ''factordb'' see http://factordb.com/index.php?id=1100000001540144907&open=ecm * the 650th Athena prime in base 14, 4D₁₉₆₉₈, which equals 5×14¹⁹⁶⁹⁸−1, ''N''+1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000884560233, for the factorization of ''N''+1 in ''factordb'' see http://factordb.com/index.php?id=1100000000884560625&open=ecm * the 2335th Athena prime in base 16, 88F₅₄₅, which equals 137×16⁵⁴⁵−1, ''N''+1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000413679658, for the factorization of ''N''+1 in ''factordb'' see http://factordb.com/index.php?id=1100000000413877337&open=ecm * the 10317th Athena prime in base 17, 5A70₂₇₄1, which equals 1622×17²⁷⁵+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000003782940709, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000003782941930&open=ecm * the 10359th Athena prime in base 17, 9D0₁₀₆₇1, which equals 166×17¹⁰⁶⁸+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000765961369, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000765961370&open=ecm * the 10370th Athena prime in base 17, A0₁₃₅₅1, which equals 10×17¹³⁵⁶+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000034167087, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000271866825&open=ecm * the 10386th Athena prime in base 17, 530₄₈₆₇1, which equals 88×17⁴⁸⁶⁸+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000762660735, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000762660737&open=ecm * the 10408th Athena prime in base 17, 570₅₁₃₁₀1, which equals 92×17⁵¹³¹¹+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000765961389, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000785469616&open=ecm * the 10412th Athena prime in base 17, 970₁₆₆₀₄₇1, which equals 160×17¹⁶⁶⁰⁴⁸+1, ''N''−1 is trivially fully factored, but it has no helper file in ''factordb'' since it is too large (>10¹⁹⁹⁹⁹⁹) to be PRP-tested in ''factordb'', for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000890817312&open=ecm * the 10413th Athena prime in base 17, F70₁₈₆₇₆₇1, which equals 262×17¹⁸⁶⁷⁶⁸+1, ''N''−1 is trivially fully factored, but it has no helper file in ''factordb'' since it is too large (>10¹⁹⁹⁹⁹⁹) to be PRP-tested in ''factordb'', for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000890817317&open=ecm * the 3310th Athena prime in base 20, JCJ₆₂₉, which equals 393×20⁶²⁹−1, ''N''+1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000001559454258, for the factorization of ''N''+1 in ''factordb'' see http://factordb.com/index.php?id=1100000001559454271&open=ecm * the 13373rd Athena prime in base 21, 5D0₁₉₈₄₈1, which equals 118×21¹⁹⁸⁴⁹+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000777265872, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000785469310&open=ecm * the 3408th Athena prime in base 24, 88N₅₉₅₁, which equals 201×24⁵⁹⁵¹−1, ''N''+1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000003593275880, for the factorization of ''N''+1 in ''factordb'' see http://factordb.com/index.php?id=1100000003593373246&open=ecm * the 25509th Athena prime in base 28, EB0₄₀₅1, which equals 403×28⁴⁰⁶+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000001534442374, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000001534442380&open=ecm * the 2616th Athena prime in base 30, C0₁₀₂₂1, which equals 12×30¹⁰²³+1, ''N''−1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000785448736, for the factorization of ''N''−1 in ''factordb'' see http://factordb.com/index.php?id=1100000000785448737&open=ecm * the 2619th Athena prime in base 30, OT₃₄₂₀₅, which equals 25×30³⁴²⁰⁵−1, ''N''+1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000800812865, for the factorization of ''N''+1 in ''factordb'' see http://factordb.com/index.php?id=1100000000819405041&open=ecm * the 35237th Athena prime in base 36, P8Z₃₉₀, which equals 909×36³⁹⁰−1, ''N''+1 is trivially fully factored, for its helper file in ''factordb'' see http://factordb.com/helper.php?id=1100000000764100228, for the factorization of ''N''+1 in ''factordb'' see http://factordb.com/index.php?id=1100000000764100231&open=ecm and the Athena primes > 10²⁹⁹ in bases ''b'' = 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 24, 26, 28, 30, 36 whose ''N''−1 or ''N''+1 is ≥ 1/3 factored: (''R''_''n''(''b'') means the [[:w:Repunit|repunit]] in base ''b'' with length ''n''), i.e. ''R''_''n''(''b'') = (''b''^''n''−1)/(''b''−1), "''S''_''n''(''b'')" means ''b''^''n''+1) * the 3168th Athena prime in base 13, 9₃₀₈1, ''N''−1 is 117×''R''₃₀₈(13), thus factor ''N''−1 is equivalent to factor the Cunningham number 13³⁰⁸−1, and for the algebraic factors of 13³⁰⁸−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showExplorer?Base=13&Exp=308&LBIDPMList=A&LBIDLODList=D, and for the prime factorization of 13³⁰⁸−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showSingleEntry?Base=13&Exp=308&c0=-&EN=&LM= * the 3179th Athena prime in base 13, B₅₆₃C, ''N''−1 is 11×''R''₅₆₄(13), thus factor ''N''−1 is equivalent to factor the Cunningham number 13⁵⁶⁴−1, and for the algebraic factors of 13⁵⁶⁴−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showExplorer?Base=13&Exp=564&LBIDPMList=A&LBIDLODList=D, and for the prime factorization of 13⁵⁶⁴−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showSingleEntry?Base=13&Exp=564&c0=-&EN=&LM= * the 3180th Athena prime in base 13, 1B₅₇₆, ''N''−1 is 23×''R''₅₇₆(13), thus factor ''N''−1 is equivalent to factor the Cunningham number 13⁵⁷⁶−1, and for the algebraic factors of 13⁵⁷⁶−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showExplorer?Base=13&Exp=576&LBIDPMList=A&LBIDLODList=D, and for the prime factorization of 13⁵⁷⁶−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showSingleEntry?Base=13&Exp=576&c0=-&EN=&LM= * the 10320th Athena prime in base 17, 9₂₉₂1, ''N''−1 is 153×''R''₂₉₂(17), thus factor ''N''−1 is equivalent to factor the Cunningham number 17²⁹²−1, and for the algebraic factors of 17²⁹²−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showExplorer?Base=17&Exp=292&LBIDPMList=A&LBIDLODList=D, and for the prime factorization of 17²⁹²−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showSingleEntry?Base=17&Exp=292&c0=-&EN=&LM= * the 13304th Athena prime in base 21, 7₂₃₀1, ''N''−1 is 147×''R''₂₃₀(21), thus factor ''N''−1 is equivalent to factor the Cunningham number 21²³⁰−1, and for the algebraic factors of 21²³⁰−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showExplorer?Base=21&Exp=230&LBIDPMList=A&LBIDLODList=D, and for the prime factorization of 21²³⁰−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showSingleEntry?Base=21&Exp=230&c0=-&EN=&LM= * the 13355th Athena prime in base 21, 3₁₀₆₃2, ''N''+1 is 3×''R''₁₀₆₄(21), thus factor ''N''−1 is equivalent to factor the Cunningham number 21¹⁰⁶⁴−1, and for the algebraic factors of 21¹⁰⁶⁴−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showExplorer?Base=21&Exp=1064&LBIDPMList=A&LBIDLODList=D, and for the prime factorization of 21¹⁰⁶⁴−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showSingleEntry?Base=21&Exp=1064&c0=-&EN=&LM= * the 25199th Athena prime in base 26, 9K₃₄₃AP, ''N''+1 is 6370×''R''₃₄₄(26), thus factor ''N''+1 is equivalent to factor the Cunningham number 26³⁴⁴−1, and for the algebraic factors of 26³⁴⁴−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showExplorer?Base=26&Exp=344&LBIDPMList=A&LBIDLODList=D, and for the prime factorization of 26³⁴⁴−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showSingleEntry?Base=26&Exp=344&c0=-&EN=&LM= * the 25200th Athena prime in base 26, 8₃₅₄1, ''N''−1 is 208×''R''₃₅₄(26), thus factor ''N''−1 is equivalent to factor the Cunningham number 26³⁵⁴−1, and for the algebraic factors of 26³⁵⁴−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showExplorer?Base=26&Exp=354&LBIDPMList=A&LBIDLODList=D, and for the prime factorization of 26³⁵⁴−1, see http://myfactorcollection.mooo.com:8090/cgi-bin/showSingleEntry?Base=26&Exp=354&c0=-&EN=&LM= All numbers are written in base ''b'', [[:w:Senary#Base 36 as senary compression|using A to Z to represent digit values 10 to 35]], "{}" means repeating, e.g. family 12{3}45 means the sequence {1245, 12345, 123345, 1233345, 12333345, 123333345, ...} (where the members are expressed as base ''b'' strings), subscripts are used to indicate repetitions of digits, e.g. 123₄567 means 123333567 (all subscripts are written in decimal). Base 2: 1 Athena prime (the largest of which has 2 digits (it is 11, and its value is 3 in decimal)): {11} Base 3: 3 Athena primes (the largest of which has 3 digits (it is 111, and its value is 13 in decimal)): {12, 21, 111} Base 4: 5 Athena primes (the largest of which has 3 digits (it is 221, and its value is 41 in decimal)): {11, 13, 23, 31, 221} Base 5: 22 Athena primes (the largest of which has 96 digits (it is 10₉₃13, and its algebraic form is 5⁹⁵+8)): {12, 21, 23, 32, 34, 43, 104, 111, 131, 133, 313, 401, 414, 3101, 10103, 14444, 30301, 33001, 33331, 44441, 300031, 100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000013} Base 6: 11 Athena primes (the largest of which has 5 digits (it is 40041, and its value is 5209 in decimal)): {11, 15, 21, 25, 31, 35, 45, 51, 4401, 4441, 40041} Base 7: 71 Athena primes (the largest of which has 17 digits (it is 3₁₆1, and its algebraic form is (7¹⁷−5)/2)): {14, 16, 23, 25, 32, 41, 43, 52, 56, 61, 65, 113, 115, 131, 133, 155, 212, 221, 304, 313, 335, 344, 346, 364, 445, 515, 533, 535, 544, 551, 553, 1022, 1051, 1112, 1202, 1211, 1222, 2111, 3031, 3055, 3334, 3503, 3505, 3545, 4504, 4555, 5011, 5455, 5545, 5554, 6034, 6634, 11111, 11201, 30011, 30101, 31001, 31111, 33001, 33311, 35555, 40054, 100121, 150001, 300053, 351101, 531101, 1100021, 33333301, 5100000001, 33333333333333331} Base 8: 75 Athena primes (the largest of which has 221 digits (it is 4₂₂₀7, and its algebraic form is (4×8²²¹+17)/7)): {13, 15, 21, 23, 27, 35, 37, 45, 51, 53, 57, 65, 73, 75, 107, 111, 117, 141, 147, 161, 177, 225, 255, 301, 343, 361, 401, 407, 417, 431, 433, 463, 467, 471, 631, 643, 661, 667, 701, 711, 717, 747, 767, 3331, 3411, 4043, 4443, 4611, 5205, 6007, 6101, 6441, 6477, 6707, 6777, 7461, 7641, 47777, 60171, 60411, 60741, 444641, 500025, 505525, 3344441, 4444477, 5500525, 5550525, 55555025, 444444441, 744444441, 77774444441, 7777777777771, 555555555555525, 44444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444444447} Base 9: 151 Athena primes (the largest of which has 1161 digits (it is 30₁₁₅₈11, and its algebraic form is 3×9¹¹⁶⁰+10)): {12, 14, 18, 21, 25, 32, 34, 41, 45, 47, 52, 58, 65, 67, 74, 78, 81, 87, 117, 131, 135, 151, 155, 175, 177, 238, 272, 308, 315, 331, 337, 355, 371, 375, 377, 438, 504, 515, 517, 531, 537, 557, 564, 601, 638, 661, 702, 711, 722, 735, 737, 751, 755, 757, 771, 805, 838, 1011, 1015, 1101, 1701, 2027, 2207, 3017, 3057, 3101, 3501, 3561, 3611, 3688, 3868, 5035, 5051, 5071, 5101, 5501, 5554, 5705, 5707, 7017, 7075, 7105, 7301, 8535, 8544, 8555, 8854, 20777, 22227, 22777, 30161, 33388, 50161, 50611, 53335, 55111, 55535, 55551, 57061, 57775, 70631, 71007, 77207, 100037, 100071, 100761, 105007, 270707, 301111, 305111, 333035, 333385, 333835, 338885, 350007, 500075, 530005, 555611, 631111, 720707, 2770007, 3030335, 7776662, 30300005, 30333335, 38333335, 51116111, 70000361, 300030005, 300033305, 351111111, 1300000007, 5161111111, 8333333335, 300000000035, 311111111161, 544444444444, 2000000000007, 5700000000001, 7270000000007, 88888888833335, 100000000000507, 5111111111111161, 7277777777777777707, 8888888888888888888335, 30000000000000000000051, 1000000000000000000000000057, 56111111111111111111111111111111111111, 7666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666662, 27777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777777707, 300000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011} Base 10: 77 Athena primes (the largest of which has 31 digits (it is 50₂₈27, and its algebraic form is 5×10³⁰+27)): {11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 227, 251, 257, 277, 281, 349, 409, 449, 499, 521, 557, 577, 587, 727, 757, 787, 821, 827, 857, 877, 881, 887, 991, 2087, 2221, 5051, 5081, 5501, 5581, 5801, 5851, 6469, 6949, 8501, 9001, 9049, 9221, 9551, 9649, 9851, 9949, 20021, 20201, 50207, 60649, 80051, 666649, 946669, 5200007, 22000001, 60000049, 66000049, 66600049, 80555551, 555555555551, 5000000000000000000000000000027} Base 11: 1068 Athena (probable) primes (including 1 unproven probable prime: 57₆₂₆₆₈), the largest of which has 62669 digits (it is 57₆₂₆₆₈, and its algebraic form is (57×11⁶²⁶⁶⁸−7)/10), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel11 Data of Athena (probable) primes base 11] Base 12: 106 Athena primes (the largest of which has 42 digits (it is 40₃₉77, and its algebraic form is 4×12⁴¹+91)): {11, 15, 17, 1B, 25, 27, 31, 35, 37, 3B, 45, 4B, 51, 57, 5B, 61, 67, 6B, 75, 81, 85, 87, 8B, 91, 95, A7, AB, B5, B7, 221, 241, 2A1, 2B1, 2BB, 401, 421, 447, 471, 497, 565, 655, 665, 701, 70B, 721, 747, 771, 77B, 797, 7A1, 7BB, 907, 90B, 9BB, A41, B21, B2B, 2001, 200B, 202B, 222B, 229B, 292B, 299B, 4441, 4707, 4777, 6A05, 6AA5, 729B, 7441, 7B41, 929B, 9777, 992B, 9947, 997B, 9997, A0A1, A201, A605, A6A5, AA65, B001, B0B1, BB01, BB41, 600A5, 7999B, 9999B, AAAA1, B04A1, B0B9B, BAA01, BAAA1, BB09B, BBBB1, 44AAA1, A00065, BBBAA1, AAA0001, B00099B, AA000001, BBBBBB99B, B0000000000000000000000000009B, 400000000000000000000000000000000000000077} Base 13: 3197 Athena (probable) primes (including 4 unproven probable primes: C5₂₃₇₅₅C, 80₃₂₀₁₇111, 95₁₉₇₄₂₀, A3₅₉₂₁₉₇A), the largest of which has 592199 digits (it is A3₅₉₂₁₉₇A, and its algebraic form is (41×13⁵⁹²¹⁹⁸+27)/4), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel13 Data of Athena (probable) primes base 13] Base 14: 650 Athena primes, the largest of which has 19699 digits (it is 4D₁₉₆₉₈, and its algebraic form is 5×14¹⁹⁶⁹⁸−1), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel14 Data of Athena primes base 14] Base 15: 1284 Athena primes, the largest of which has 157 digits (it is 7₁₅₅97, and its algebraic form is (15¹⁵⁷+59)/2), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel15 Data of Athena primes base 15] Base 16: 2347 Athena (probable) primes (including 3 unproven probable primes: DB₃₂₂₃₄, 4₇₂₇₈₅DD, 3₁₁₆₁₃₇AF), the largest of which has 116139 digits (it is 3₁₁₆₁₃₇AF, and its algebraic form is (16¹¹⁶¹³⁹+619)/5), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel16 Data of Athena (probable) primes base 16] Base 17: 10415 known Athena (probable) primes (including many unproven probable primes) and 12 unsolved families (1{7}, 1F{0}7, 4{7}A, 70F{0}D, 8{B}9, 9{5}9, A{D}F, B{0}B3, {B}E9, {B}EE, F1{9}, FD0{D}, no primes or probable primes with length ≤ 200000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel17 Data of known Athena (probable) primes base 17] Base 18: 549 Athena primes, the largest of which has 6271 digits (it is C0₆₂₆₈C5, and its algebraic form is 12×18⁶²⁷⁰+221), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel18 Data of Athena primes base 18] Base 19: 31417 known Athena (probable) primes (including many unproven probable primes) and 17 unsolved families (4B5{0}H, {5}3, 5{H}05, 5{H}0H, 5{H}5, 66{B}, 71{0}177, 7AF{0}H, 97{0}3, C{H}C, EE1{6}, F{7}5, F{B}G, F{D}F, H0F{0}7A, HB{0}5B5, II{D}, no primes or probable primes with length ≤ 200000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel19 Data of known Athena (probable) primes base 19] Base 20: 3314 Athena primes, the largest of which has 6271 digits (it is G0₆₂₆₉D, and its algebraic form is 16×20⁶²⁷⁰+13), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel20 Data of Athena primes base 20] Base 21: 13386 known Athena (probable) primes (including many unproven probable primes) and 8 unsolved families (5{0}DJ, {9}D, B3{0}EB, B{H}6H, C{F}0K, {F}35, G{0}FK, H{0}7771, no primes or probable primes with length ≤ 200000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel21 Data of known Athena (probable) primes base 21] Base 22: 8003 Athena (probable) primes (including 1 unproven probable prime: BK₂₂₀₀₁5), the largest of which has 22003 digits (it is BK₂₂₀₀₁5, and its algebraic form is (251×22²²⁰⁰²−335)/21), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel22 Data of Athena (probable) primes base 22] Base 23: 65178 known Athena (probable) primes (including many unproven probable primes) and 87 unsolved families (no primes or probable primes with length ≤ 100000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel23 Data of known Athena (probable) primes base 23] and [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/left23 Data of unsolved families for Athena problem base 23] Base 24: 3409 Athena primes, the largest of which has 8134 digits (it is N00N₈₁₂₉LN, and its algebraic form is 13249×24⁸¹³¹−49), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel24 Data of Athena primes base 24] Base 25: 133639 known Athena (probable) primes (including many unproven probable primes) and 85 unsolved families (no primes or probable primes with length ≤ 100000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel25 Data of known Athena (probable) primes base 25] and [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/left25 Data of unsolved families for Athena problem base 25] Base 26: 25256 known Athena (probable) primes (including 7 unproven probable primes: 5₁₉₃₉₁6F, 7₂₀₂₇₉OL, LD0₂₀₉₇₅7, 6K₂₃₃₀₀5, J0₄₄₃₀₃KCB, M0₆₁₁₈₆2BB, 85M₁₉₇₀₆₀B) and 3 unsolved families ({A}6F, {H}MH, {I}GL, no primes or probable primes with length ≤ 200000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel26 Data of known Athena (probable) primes base 26] Base 27: 102852 known Athena (probable) primes (including many unproven probable primes) and 44 unsolved families (no primes or probable primes with length ≤ 100000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel27 Data of known Athena (probable) primes base 27] and [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/left27 Data of unsolved families for Athena problem base 27] Base 28: 25528 known Athena (probable) primes (including 3 unproven probable primes: N6₂₄₀₅₁LR, 5OA₃₁₂₃₈F, O4O₉₄₅₃₅9) and 1 unsolved family (O{A}F, no primes or probable primes with length ≤ 900000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel28 Data of known Athena (probable) primes base 28] Base 29: 355242 known Athena (probable) primes (including many unproven probable primes) and 125 unsolved families (no primes or probable primes with length ≤ 100000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel29 Data of known Athena (probable) primes base 29] and [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/left29 Data of unsolved families for Athena problem base 29] Base 30: 2619 Athena (probable) primes (including 1 unproven probable prime: I0₂₄₆₀₈D), the largest of which has 34206 digits (it is OT₃₄₂₀₅, and its algebraic form is 25×30³⁴²⁰⁵−1), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel30 Data of Athena (probable) primes base 30] Base 31: 569323 known Athena (probable) primes (including many unproven probable primes) and 77 unsolved families (no primes or probable primes with length ≤ 100000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel31 Data of known Athena (probable) primes base 31] and [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/left31 Data of unsolved families for Athena problem base 31] Base 32: 168882 known Athena (probable) primes (including many unproven probable primes) and 120 unsolved families (no primes or probable primes with length ≤ 100000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel32 Data of known Athena (probable) primes base 32] and [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/left32 Data of unsolved families for Athena problem base 32] Base 33: 280012 known Athena (probable) primes (including many unproven probable primes) and 81 unsolved families (no primes or probable primes with length ≤ 100000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel33 Data of known Athena (probable) primes base 33] and [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/left33 Data of unsolved families for Athena problem base 33] Base 34: 184785 known Athena (probable) primes (including many unproven probable primes) and 47 unsolved families (no primes or probable primes with length ≤ 100000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel34 Data of known Athena (probable) primes base 34] and [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/left34 Data of unsolved families for Athena problem base 34] Base 35: 720002 known Athena (probable) primes (including many unproven probable primes) and 60 unsolved families (no primes or probable primes with length ≤ 100000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel35 Data of known Athena (probable) primes base 35] and [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/left35 Data of unsolved families for Athena problem base 35] Base 36: 35286 known Athena (probable) primes (including 3 unproven probable primes: 7K₂₆₅₆₇Z, S0₇₅₀₀₇8H, P₈₁₉₉₃SZ) and 4 unsolved families (B{0}EUV, HM{0}N, N{0}YYN, O{L}Z, no primes or probable primes with length ≤ 200000, nor can be proven to only contain composites), see [https://raw.githubusercontent.com/xayahrainie4793/minimal-elements-of-the-prime-numbers/main/kernel36 Data of known Athena (probable) primes base 36] == Condensed table for bases 2 ≤ ''b'' ≤ 36 == {|class="wikitable" ||''b''||number of Athena primes (or probable primes, which are Athena primes assuming their primality) in base ''b''||base-''b'' form of the top 10 known Athena primes (or probable primes, which are Athena primes assuming their primality) in base ''b'' (write "''d''_''n''" if there are 5 or more (''n'') consecutive same digits ''d'')||length of the top 10 known Athena primes (or probable primes, which are Athena primes assuming their primality) in base ''b''||length of the top 10 known Athena primes (or probable primes, which are Athena primes assuming their primality) in base ''b'' in decimal||algebraic ((''a''×''b''^''n''+''c'')/''gcd''(''a''+''c'',''b''−1)) form of the top 10 known Athena primes (or probable primes, which are Athena primes assuming their primality) in base ''b''||''factordb'' entry of the top 10 known Athena primes (or probable primes, which are Athena primes assuming their primality) in base ''b''||the top 10 known Athena primes (or probable primes, which are Athena primes assuming their primality) in base ''b'' written in base ''b'' (use lower case letters instead of upper case letters)||number of unsolved families in the Athena problem in base ''b'' (all of these left families are linear families)||searching limit of length for the unsolved families in the Athena problem in base ''b'' (if there are different searching limits for the unsolved families in the Athena problem in base ''b'', choose the lowest searching limit)|| |- ||2||1||11||2||1||3||http://factordb.com/index.php?id=3&open=ecm||http://factordb.com/index.php?showid=3&base=2||0||–|| |- ||3||3||111<br>21<br>12||3<br>2<br>2||2<br>1<br>1||13<br>7<br>5||http://factordb.com/index.php?id=13&open=ecm<br>http://factordb.com/index.php?id=7&open=ecm<br>http://factordb.com/index.php?id=5&open=ecm<nowiki/>||http://factordb.com/index.php?showid=13&base=3<br>http://factordb.com/index.php?showid=7&base=3<br>http://factordb.com/index.php?showid=5&base=3<nowiki/>||0||–|| |- ||4||5||221<br>31<br>23<br>13<br>11||3<br>2<br>2<br>2<br>2||2<br>2<br>2<br>1<br>1||41<br>13<br>11<br>7<br>5||http://factordb.com/index.php?id=41&open=ecm<br>http://factordb.com/index.php?id=13&open=ecm<br>http://factordb.com/index.php?id=11&open=ecm<br>http://factordb.com/index.php?id=7&open=ecm<br>http://factordb.com/index.php?id=5&open=ecm<nowiki/>||http://factordb.com/index.php?showid=41&base=4<br>http://factordb.com/index.php?showid=13&base=4<br>http://factordb.com/index.php?showid=11&base=4<br>http://factordb.com/index.php?showid=7&base=4<br>http://factordb.com/index.php?showid=5&base=4<nowiki/>||0||–|| |- ||5||22||10₉₃13<br>300031<br>44441<br>33331<br>33001<br>30301<br>14444<br>10103<br>3101<br>414||96<br>6<br>5<br>5<br>5<br>5<br>5<br>5<br>4<br>3||67<br>4<br>4<br>4<br>4<br>4<br>4<br>3<br>3<br>3||5⁹⁵+8<br>9391<br>3121<br>2341<br>2251<br>1951<br>1249<br>653<br>401<br>109||http://factordb.com/index.php?id=1100000000034686071&open=ecm<br>http://factordb.com/index.php?id=9391&open=ecm<br>http://factordb.com/index.php?id=3121&open=ecm<br>http://factordb.com/index.php?id=2341&open=ecm<br>http://factordb.com/index.php?id=2251&open=ecm<br>http://factordb.com/index.php?id=1951&open=ecm<br>http://factordb.com/index.php?id=1249&open=ecm<br>http://factordb.com/index.php?id=653&open=ecm<br>http://factordb.com/index.php?id=401&open=ecm<br>http://factordb.com/index.php?id=109&open=ecm<nowiki/>||http://factordb.com/index.php?showid=1100000000034686071&base=5<br>http://factordb.com/index.php?showid=9391&base=5<br>http://factordb.com/index.php?showid=3121&base=5<br>http://factordb.com/index.php?showid=2341&base=5<br>http://factordb.com/index.php?showid=2251&base=5<br>http://factordb.com/index.php?showid=1951&base=5<br>http://factordb.com/index.php?showid=1249&base=5<br>http://factordb.com/index.php?showid=653&base=5<br>http://factordb.com/index.php?showid=401&base=5<br>http://factordb.com/index.php?showid=109&base=5<nowiki/>||0||–|| |- ||6||11||40041<br>4441<br>4401<br>51<br>45<br>35<br>31<br>25<br>21<br>15||5<br>4<br>4<br>2<br>2<br>2<br>2<br>2<br>2<br>2||4<br>4<br>4<br>2<br>2<br>2<br>2<br>2<br>2<br>2||5209<br>1033<br>1009<br>31<br>29<br>23<br>19<br>17<br>13<br>11||http://factordb.com/index.php?id=5209&open=ecm<br>http://factordb.com/index.php?id=1033&open=ecm<br>http://factordb.com/index.php?id=1009&open=ecm<br>http://factordb.com/index.php?id=31&open=ecm<br>http://factordb.com/index.php?id=29&open=ecm<br>http://factordb.com/index.php?id=23&open=ecm<br>http://factordb.com/index.php?id=19&open=ecm<br>http://factordb.com/index.php?id=17&open=ecm<br>http://factordb.com/index.php?id=13&open=ecm<br>http://factordb.com/index.php?id=11&open=ecm<nowiki/>||http://factordb.com/index.php?showid=5209&base=6<br>http://factordb.com/index.php?showid=1033&base=6<br>http://factordb.com/index.php?showid=1009&base=6<br>http://factordb.com/index.php?showid=31&base=6<br>http://factordb.com/index.php?showid=29&base=6<br>http://factordb.com/index.php?showid=23&base=6<br>http://factordb.com/index.php?showid=19&base=6<br>http://factordb.com/index.php?showid=17&base=6<br>http://factordb.com/index.php?showid=13&base=6<br>http://factordb.com/index.php?showid=11&base=6<nowiki/>||0||–|| |- ||7||71||3₁₆1<br>510₇1<br>3₆01<br>1100021<br>531101<br>351101<br>300053<br>150001<br>100121<br>40054||17<br>10<br>8<br>7<br>6<br>6<br>6<br>6<br>6<br>5||15<br>9<br>7<br>6<br>5<br>5<br>5<br>5<br>5<br>4||(7¹⁷−5)/2<br>36×7⁸+1<br>(7⁸−47)/2<br>134471<br>91631<br>62819<br>50459<br>28813<br>16871<br>9643||http://factordb.com/index.php?id=116315256993601&open=ecm<br>http://factordb.com/index.php?id=207532837&open=ecm<br>http://factordb.com/index.php?id=2882377&open=ecm<br>http://factordb.com/index.php?id=134471&open=ecm<br>http://factordb.com/index.php?id=91631&open=ecm<br>http://factordb.com/index.php?id=62819&open=ecm<br>http://factordb.com/index.php?id=50459&open=ecm<br>http://factordb.com/index.php?id=28813&open=ecm<br>http://factordb.com/index.php?id=16871&open=ecm<br>http://factordb.com/index.php?id=9643&open=ecm<nowiki/>||http://factordb.com/index.php?showid=116315256993601&base=7<br>http://factordb.com/index.php?showid=207532837&base=7<br>http://factordb.com/index.php?showid=2882377&base=7<br>http://factordb.com/index.php?showid=134471&base=7<br>http://factordb.com/index.php?showid=91631&base=7<br>http://factordb.com/index.php?showid=62819&base=7<br>http://factordb.com/index.php?showid=50459&base=7<br>http://factordb.com/index.php?showid=28813&base=7<br>http://factordb.com/index.php?showid=16871&base=7<br>http://factordb.com/index.php?showid=9643&base=7<nowiki/>||0||–|| |- ||8||75||4₂₂₀7<br>5₁₃25<br>7₁₂1<br>77774₆1<br>74₇1<br>4₈1<br>5₅025<br>5550525<br>5500525<br>4₅77||221<br>15<br>13<br>11<br>9<br>9<br>8<br>7<br>7<br>7||200<br>14<br>12<br>10<br>9<br>8<br>8<br>7<br>7<br>7||(4×8²²¹+17)/7<br>(5×8¹⁵−173)/7<br>8¹³−7<br>(28669×8⁷−25)/7<br>(53×8⁸−25)/7<br>(4×8⁹−25)/7<br>(5×8⁸−2413)/7<br>1495381<br>1474901<br>(4×8⁷+185)/7||http://factordb.com/index.php?id=1100000000416605822&open=ecm<br>http://factordb.com/index.php?id=25131694349141&open=ecm<br>http://factordb.com/index.php?id=549755813881&open=ecm<br>http://factordb.com/index.php?id=8589035809&open=ecm<br>http://factordb.com/index.php?id=127027489&open=ecm<br>http://factordb.com/index.php?id=76695841&open=ecm<br>http://factordb.com/index.php?id=11983381&open=ecm<br>http://factordb.com/index.php?id=1495381&open=ecm<br>http://factordb.com/index.php?id=1474901&open=ecm<br>http://factordb.com/index.php?id=1198399&open=ecm<nowiki/>||http://factordb.com/index.php?showid=1100000000416605822&base=8<br>http://factordb.com/index.php?showid=25131694349141&base=8<br>http://factordb.com/index.php?showid=549755813881&base=8<br>http://factordb.com/index.php?showid=8589035809&base=8<br>http://factordb.com/index.php?showid=127027489&base=8<br>http://factordb.com/index.php?showid=76695841&base=8<br>http://factordb.com/index.php?showid=11983381&base=8<br>http://factordb.com/index.php?showid=1495381&base=8<br>http://factordb.com/index.php?showid=1474901&base=8<br>http://factordb.com/index.php?showid=1198399&base=8<nowiki/>||0||–|| |- ||9||151||30₁₁₅₈11<br>27₆₈₆07<br>76₃₂₉2<br>561₃₆<br>10₂₅57<br>30₂₀51<br>8₁₉335<br>727₁₅07<br>51₁₃61<br>10₁₁507||1161<br>689<br>331<br>38<br>28<br>23<br>22<br>19<br>16<br>15||1108<br>657<br>316<br>37<br>26<br>22<br>21<br>19<br>16<br>14||3×9¹¹⁶⁰+10<br>(23×9⁶⁸⁸−511)/8<br>(31×9³³⁰−19)/4<br>(409×9³⁶−1)/8<br>9²⁷+52<br>3×9²²+46<br>9²²−454<br>(527×9¹⁷−511)/8<br>(41×9¹⁵+359)/8<br>9¹⁴+412||http://factordb.com/index.php?id=1100000002376318423&open=prime<br>http://factordb.com/index.php?id=1100000002495467486&open=prime<br>http://factordb.com/index.php?id=1100000002359003642&open=prime<br>http://factordb.com/index.php?id=1100000001554010824&open=ecm<br>http://factordb.com/index.php?id=1100000002512830927&open=ecm<br>http://factordb.com/index.php?id=1100000000032261811&open=ecm<br>http://factordb.com/index.php?id=1100000002495736583&open=ecm<br>http://factordb.com/index.php?id=1100000003446800389&open=ecm<br>http://factordb.com/index.php?id=1055192051985121&open=ecm<br>http://factordb.com/index.php?id=22876792455373&open=ecm<nowiki/>||http://factordb.com/index.php?showid=1100000002376318423&base=9<br>http://factordb.com/index.php?showid=1100000002495467486&base=9<br>http://factordb.com/index.php?showid=1100000002359003642&base=9<br>http://factordb.com/index.php?showid=1100000001554010824&base=9<br>http://factordb.com/index.php?showid=1100000002512830927&base=9<br>http://factordb.com/index.php?showid=1100000000032261811&base=9<br>http://factordb.com/index.php?showid=1100000002495736583&base=9<br>http://factordb.com/index.php?showid=1100000003446800389&base=9<br>http://factordb.com/index.php?showid=1055192051985121&base=9<br>http://factordb.com/index.php?showid=22876792455373&base=9<nowiki/>||0||–|| |- 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|- 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|- ||12||106||40₃₉77<br>B0₂₇9B<br>B₆99B<br>AA0₅1<br>B00099B<br>AAA0001<br>BBBAA1<br>A00065<br>44AAA1<br>BBBB1||42<br>30<br>9<br>8<br>7<br>7<br>6<br>6<br>6<br>5||45<br>33<br>10<br>9<br>8<br>8<br>7<br>7<br>7<br>6||4×12⁴¹+91<br>11×12²⁹+119<br>12⁹−313<br>130×12⁶+1<br>32847239<br>32555521<br>2985817<br>2488397<br>1097113<br>248821||http://factordb.com/index.php?id=1100000002375054575&open=ecm<br>http://factordb.com/index.php?id=1100000002354113100&open=ecm<br>http://factordb.com/index.php?id=5159780039&open=ecm<br>http://factordb.com/index.php?id=388177921&open=ecm<br>http://factordb.com/index.php?id=32847239&open=ecm<br>http://factordb.com/index.php?id=32555521&open=ecm<br>http://factordb.com/index.php?id=2985817&open=ecm<br>http://factordb.com/index.php?id=2488397&open=ecm<br>http://factordb.com/index.php?id=1097113&open=ecm<br>http://factordb.com/index.php?id=248821&open=ecm<nowiki/>||http://factordb.com/index.php?showid=1100000002375054575&base=12<br>http://factordb.com/index.php?showid=1100000002354113100&base=12<br>http://factordb.com/index.php?showid=5159780039&base=12<br>http://factordb.com/index.php?showid=388177921&base=12<br>http://factordb.com/index.php?showid=32847239&base=12<br>http://factordb.com/index.php?showid=32555521&base=12<br>http://factordb.com/index.php?showid=2985817&base=12<br>http://factordb.com/index.php?showid=2488397&base=12<br>http://factordb.com/index.php?showid=1097113&base=12<br>http://factordb.com/index.php?showid=248821&base=12<nowiki/>||0||–|| |- 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|- ||14||650||4D₁₉₆₉₈<br>34D₇₀₈<br>8D₁₄₁85<br>8₈₆B<br>40₈₃49<br>8C₇₉3<br>18₇₉B<br>6B₇₇2B<br>4₆₃09<br>A₅₉3||19699<br>710<br>144<br>87<br>86<br>81<br>81<br>80<br>65<br>60||22578<br>814<br>165<br>100<br>99<br>93<br>92<br>92<br>74<br>69||5×14¹⁹⁶⁹⁸−1<br>47×14⁷⁰⁸−1<br>9×14¹⁴³−79<br>(8×14⁸⁷+31)/13<br>4×14⁸⁵+65<br>(116×14⁸⁰−129)/13<br>(21×14⁸⁰+31)/13<br>(89×14⁷⁹−1649)/13<br>(4×14⁶⁵−667)/13<br>(10×14⁶⁰−101)/13||http://factordb.com/index.php?id=1100000000884560233&open=prime<br>http://factordb.com/index.php?id=1100000001540144903&open=prime<br>http://factordb.com/index.php?id=1100000003575856650&open=ecm<br>http://factordb.com/index.php?id=1100000002321014379&open=ecm<br>http://factordb.com/index.php?id=1100000000823937973&open=ecm<br>http://factordb.com/index.php?id=1100000002631073246&open=ecm<br>http://factordb.com/index.php?id=1100000002384401372&open=ecm<br>http://factordb.com/index.php?id=1100000002631077787&open=ecm<br>http://factordb.com/index.php?id=1100000000840126683&open=ecm<br>http://factordb.com/index.php?id=1100000002321038522&open=ecm<nowiki/>||http://factordb.com/index.php?showid=1100000000884560233&base=14<br>http://factordb.com/index.php?showid=1100000001540144903&base=14<br>http://factordb.com/index.php?showid=1100000003575856650&base=14<br>http://factordb.com/index.php?showid=1100000002321014379&base=14<br>http://factordb.com/index.php?showid=1100000000823937973&base=14<br>http://factordb.com/index.php?showid=1100000002631073246&base=14<br>http://factordb.com/index.php?showid=1100000002384401372&base=14<br>http://factordb.com/index.php?showid=1100000002631077787&base=14<br>http://factordb.com/index.php?showid=1100000000840126683&base=14<br>http://factordb.com/index.php?showid=1100000002321038522&base=14<nowiki/>||0||–|| |- ||15||1284||7₁₅₅97<br>E₁₄₅397<br>96₁₀₄08<br>7₇₃CE<br>7₅₉CCE<br>50₃₃17<br>EB₃₁<br>6330₂₆1<br>7050₂₄B<br>B70₂₄1||157<br>148<br>107<br>75<br>62<br>36<br>32<br>30<br>28<br>27||185<br>175<br>126<br>88<br>73<br>42<br>38<br>35<br>33<br>32||(15¹⁵⁷+59)/2<br>15¹⁴⁸−2558<br>(66×15¹⁰⁶−619)/7<br>(15⁷⁵+163)/2<br>(15⁶²+2413)/2<br>5×15³⁵+22<br>(207×15³¹−11)/14<br>1398×15²⁷+1<br>1580×15²⁵+11<br>172×15²⁵+1||http://factordb.com/index.php?id=1100000002454891840&open=ecm<br>http://factordb.com/index.php?id=1100000002454900849&open=ecm<br>http://factordb.com/index.php?id=1100000000823937997&open=ecm<br>http://factordb.com/index.php?id=1100000003588407143&open=ecm<br>http://factordb.com/index.php?id=1100000003588407386&open=ecm<br>http://factordb.com/index.php?id=1100000002632398579&open=ecm<br>http://factordb.com/index.php?id=1100000002321033312&open=ecm<br>http://factordb.com/index.php?id=1100000002391199877&open=ecm<br>http://factordb.com/index.php?id=1100000003588407806&open=ecm<br>http://factordb.com/index.php?id=1100000000851967288&open=ecm<nowiki/>||http://factordb.com/index.php?showid=1100000002454891840&base=15<br>http://factordb.com/index.php?showid=1100000002454900849&base=15<br>http://factordb.com/index.php?showid=1100000000823937997&base=15<br>http://factordb.com/index.php?showid=1100000003588407143&base=15<br>http://factordb.com/index.php?showid=1100000003588407386&base=15<br>http://factordb.com/index.php?showid=1100000002632398579&base=15<br>http://factordb.com/index.php?showid=1100000002321033312&base=15<br>http://factordb.com/index.php?showid=1100000002391199877&base=15<br>http://factordb.com/index.php?showid=1100000003588407806&base=15<br>http://factordb.com/index.php?showid=1100000000851967288&base=15<nowiki/>||0||–|| |- ||16||2347||3₁₁₆₁₃₇AF<br>4₇₂₇₈₅DD<br>DB₃₂₂₃₄<br>D0B₁₇₈₀₄<br>5BC₃₇₀₀D<br>90₃₅₄₂91<br>300F₁₉₆₀AF<br>20₁₇₁₃321<br>F8₁₅₁₇F<br>FAF₁₀₆₂45||116139<br>72787<br>32235<br>17806<br>3703<br>3545<br>1965<br>1717<br>1519<br>1066||139845<br>87644<br>38815<br>21441<br>4459<br>4269<br>2366<br>2067<br>1830<br>1284||(16¹¹⁶¹³⁹+619)/5<br>(4×16⁷²⁷⁸⁷+2291)/15<br>(206×16³²²³⁴−11)/15<br>(3131×16¹⁷⁸⁰⁴−11)/15<br>(459×16³⁷⁰¹+1)/5<br>9×16³⁵⁴⁴+145<br>769×16¹⁹⁶²−81<br>2×16¹⁷¹⁶+801<br>(233×16¹⁵¹⁸+97)/15<br>251×16¹⁰⁶⁴−187||http://factordb.com/index.php?id=1100000003851731988&open=prime<br>http://factordb.com/index.php?id=1100000003615909841&open=prime<br>http://factordb.com/index.php?id=1100000002383583629&open=prime<br>http://factordb.com/index.php?id=1100000003589278511&open=prime<br>http://factordb.com/index.php?id=1100000000993764322&open=prime<br>http://factordb.com/index.php?id=1100000000633424191&open=prime<br>http://factordb.com/index.php?id=1100000003588368750&open=prime<br>http://factordb.com/index.php?id=1100000003588386735&open=prime<br>http://factordb.com/index.php?id=1100000000633744824&open=prime<br>http://factordb.com/index.php?id=1100000003588387610&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000003851731988&base=16<br>http://factordb.com/index.php?showid=1100000003615909841&base=16<br>http://factordb.com/index.php?showid=1100000002383583629&base=16<br>http://factordb.com/index.php?showid=1100000003589278511&base=16<br>http://factordb.com/index.php?showid=1100000000993764322&base=16<br>http://factordb.com/index.php?showid=1100000000633424191&base=16<br>http://factordb.com/index.php?showid=1100000003588368750&base=16<br>http://factordb.com/index.php?showid=1100000003588386735&base=16<br>http://factordb.com/index.php?showid=1100000000633744824&base=16<br>http://factordb.com/index.php?showid=1100000003588387610&base=16<nowiki/>||0||–|| |- ||17||10415~10427||95F₁₉₈₈₅₅<br>B0₁₈₉₀₈₃DB<br>F70₁₈₆₇₆₇1<br>970₁₆₆₀₄₇1<br>510₁₂₄₀₇₄D<br>49₁₁₁₃₃₃<br>B₆₇₁₀₃2E<br>570₅₁₃₁₀1<br>E9B₄₄₇₃₂<br>D0GD₃₇₀₉₆||198857<br>189086<br>186770<br>166050<br>124077<br>111334<br>67105<br>51313<br>44734<br>37099||244684<br>232661<br>229811<br>204316<br>152670<br>136991<br>82570<br>63138<br>55043<br>45649||(2543×17¹⁹⁸⁸⁵⁵−15)/16<br>11×17¹⁸⁹⁰⁸⁵+232<br>262×17¹⁸⁶⁷⁶⁸+1<br>160×17¹⁶⁶⁰⁴⁸+1<br>86×17¹²⁴⁰⁷⁵+13<br>(73×17¹¹¹³³³−9)/16<br>(11×17⁶⁷¹⁰⁵−2411)/16<br>92×17⁵¹³¹¹+1<br>(3963×17⁴⁴⁷³²−11)/16<br>(60381×17³⁷⁰⁹⁶−13)/16||http://factordb.com/index.php?id=1100000008610514108&open=prime<br>http://factordb.com/index.php?id=1100000008610515753&open=prime<br>http://factordb.com/index.php?id=1100000000765961429&open=prime<br>http://factordb.com/index.php?id=1100000000765961411&open=prime<br>http://factordb.com/index.php?id=1100000008610516879&open=prime<br>http://factordb.com/index.php?id=1100000000808118219&open=prime<br>http://factordb.com/index.php?id=1100000003993647842&open=prime<br>http://factordb.com/index.php?id=1100000000765961389&open=prime<br>http://factordb.com/index.php?id=1100000003883765450&open=prime<br>http://factordb.com/index.php?id=1100000003848346668&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000008610514108&base=17<br>http://factordb.com/index.php?showid=1100000008610515753&base=17<br>http://factordb.com/index.php?showid=1100000000765961429&base=17<br>http://factordb.com/index.php?showid=1100000000765961411&base=17<br>http://factordb.com/index.php?showid=1100000008610516879&base=17<br>http://factordb.com/index.php?showid=1100000000808118219&base=17<br>http://factordb.com/index.php?showid=1100000003993647842&base=17<br>http://factordb.com/index.php?showid=1100000000765961389&base=17<br>http://factordb.com/index.php?showid=1100000003883765450&base=17<br>http://factordb.com/index.php?showid=1100000003848346668&base=17<nowiki/>||12||200000|| |- ||18||549||C0₆₂₆₈C5<br>H₇₆₆FH<br>80₂₉₈B<br>C0₁₁₆F5<br>HD₉₃<br>GG0₃₀1<br>CF₃₀5<br>B₁₉6B<br>CCF₁₄5<br>7₁₄G7||6271<br>768<br>300<br>119<br>94<br>33<br>32<br>21<br>17<br>16||7872<br>965<br>377<br>150<br>118<br>42<br>41<br>27<br>22<br>20||12×18⁶²⁷⁰+221<br>18⁷⁶⁸−37<br>8×18²⁹⁹+11<br>12×18¹¹⁸+275<br>(302×18⁹³−13)/17<br>304×18³¹+1<br>(219×18³¹−185)/17<br>(11×18²¹−1541)/17<br>(3891×18¹⁵−185)/17<br>(7×18¹⁶+2747)/17||http://factordb.com/index.php?id=1100000003590442437&open=prime<br>http://factordb.com/index.php?id=1100000003590430490&open=prime<br>http://factordb.com/index.php?id=1100000002355574745&open=prime<br>http://factordb.com/index.php?id=1100000002632837015&open=ecm<br>http://factordb.com/index.php?id=1100000002321052894&open=ecm<br>http://factordb.com/index.php?id=1100000000819230161&open=ecm<br>http://factordb.com/index.php?id=1100000002631240657&open=ecm<br>http://factordb.com/index.php?id=1100000003590430474&open=ecm<br>http://factordb.com/index.php?id=1100000003590430470&open=ecm<br>http://factordb.com/index.php?id=1100000003590430465&open=ecm<nowiki/>||http://factordb.com/index.php?showid=1100000003590442437&base=18<br>http://factordb.com/index.php?showid=1100000003590430490&base=18<br>http://factordb.com/index.php?showid=1100000002355574745&base=18<br>http://factordb.com/index.php?showid=1100000002632837015&base=18<br>http://factordb.com/index.php?showid=1100000002321052894&base=18<br>http://factordb.com/index.php?showid=1100000000819230161&base=18<br>http://factordb.com/index.php?showid=1100000002631240657&base=18<br>http://factordb.com/index.php?showid=1100000003590430474&base=18<br>http://factordb.com/index.php?showid=1100000003590430470&base=18<br>http://factordb.com/index.php?showid=1100000003590430465&base=18<nowiki/>||0||–|| |- ||19||31417~31434||1E70₁₂₂₈₉₆1<br>40₁₂₁₈₄₆HB5<br>35₁₂₀₅₆₂<br>FH0H₁₁₂₆₅₉<br>FG6₁₁₀₉₈₄<br>H₈₆₂₉₁6<br>D90₇₃₀₄₆9<br>4F0₄₉₈₄₇6<br>2₄₈₂₂₄7<br>2₄₅₈₈₆7A||122900<br>121850<br>120563<br>112662<br>110986<br>86292<br>73049<br>49850<br>48225<br>45888||157158<br>155816<br>154170<br>144067<br>110347<br>141924<br>93412<br>63746<br>61667<br>58679||634×19¹²²⁸⁹⁷+1<br>4×19¹²¹⁸⁴⁹+6351<br>(59×19¹²⁰⁵⁶²−5)/18<br>(103301×19¹¹²⁶⁵⁹−17)/18<br>(904×19¹¹⁰⁹⁸⁴−1)/3<br>(17×19⁸⁶²⁹²−215)/18<br>256×19⁷³⁰⁴⁷+9<br>91×19⁴⁹⁸⁴⁸+6<br>(19⁴⁸²²⁵+44)/9<br>(19⁴⁵⁸⁸⁸+926)/9||http://factordb.com/index.php?id=1100000001582289581&open=prime<br>http://factordb.com/index.php?id=1100000008755307222&open=prime<br>http://factordb.com/index.php?id=1100000005513825027&open=prime<br>http://factordb.com/index.php?id=1100000008755311453&open=prime<br>http://factordb.com/index.php?id=1100000000808118212&open=prime<br>http://factordb.com/index.php?id=1100000004163040839&open=prime<br>http://factordb.com/index.php?id=1100000003998413751&open=prime<br>http://factordb.com/index.php?id=1100000000808118332&open=prime<br>http://factordb.com/index.php?id=1100000003949188041&open=prime<br>http://factordb.com/index.php?id=1100000003949189035&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000001582289581&base=19<br>http://factordb.com/index.php?showid=1100000008755307222&base=19<br>http://factordb.com/index.php?showid=1100000005513825027&base=19<br>http://factordb.com/index.php?showid=1100000008755311453&base=19<br>http://factordb.com/index.php?showid=1100000000808118212&base=19<br>http://factordb.com/index.php?showid=1100000004163040839&base=19<br>http://factordb.com/index.php?showid=1100000003998413751&base=19<br>http://factordb.com/index.php?showid=1100000000808118332&base=19<br>http://factordb.com/index.php?showid=1100000003949188041&base=19<br>http://factordb.com/index.php?showid=1100000003949189035&base=19<nowiki/>||17||200000|| |- ||20||3314||G0₆₂₆₉D<br>CD₂₄₄₉<br>50₁₁₆₃AJ<br>J₆₅₅05J<br>JCJ₆₂₉<br>E₅₆₆C7<br>3A₅₂₇3<br>G₄₄₇99<br>EC0₄₂₉7<br>40₃₈₇404B||6271<br>2450<br>1166<br>658<br>631<br>568<br>529<br>449<br>432<br>392||8159<br>3188<br>1517<br>857<br>821<br>739<br>688<br>585<br>562<br>510||16×20⁶²⁷⁰+13<br>(241×20²⁴⁴⁹−13)/19<br>5×20¹¹⁶⁵+219<br>20⁶⁵⁸−7881<br>393×20⁶²⁹−1<br>(14×20⁵⁶⁸−907)/19<br>(67×20⁵²⁸−143)/19<br>(16×20⁴⁴⁹−2809)/19<br>292×20⁴³⁰+7<br>4×20³⁹¹+32091||http://factordb.com/index.php?id=1100000003590539457&open=prime<br>http://factordb.com/index.php?id=1100000002325393915&open=prime<br>http://factordb.com/index.php?id=1100000003590502412&open=prime<br>http://factordb.com/index.php?id=1100000003590502490&open=prime<br>http://factordb.com/index.php?id=1100000001559454258&open=prime<br>http://factordb.com/index.php?id=1100000003590502516&open=prime<br>http://factordb.com/index.php?id=1100000003590502531&open=prime<br>http://factordb.com/index.php?id=1100000000840126753&open=prime<br>http://factordb.com/index.php?id=1100000002633348702&open=prime<br>http://factordb.com/index.php?id=1100000003590502563&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000003590539457&base=20<br>http://factordb.com/index.php?showid=1100000002325393915&base=20<br>http://factordb.com/index.php?showid=1100000003590502412&base=20<br>http://factordb.com/index.php?showid=1100000003590502490&base=20<br>http://factordb.com/index.php?showid=1100000001559454258&base=20<br>http://factordb.com/index.php?showid=1100000003590502516&base=20<br>http://factordb.com/index.php?showid=1100000003590502531&base=20<br>http://factordb.com/index.php?showid=1100000000840126753&base=20<br>http://factordb.com/index.php?showid=1100000002633348702&base=20<br>http://factordb.com/index.php?showid=1100000003590502563&base=20<nowiki/>||0||–|| |- ||21||13386~13394||27₁₈₄₄₉₉9D<br>F9₁₇₈₇₇₁D<br>2FC₁₁₂₀₂₂A<br>7₁₀₈₄₅₀ID<br>40₄₇₃₃₃9G<br>B90₄₅₀₁₉E5<br>HD₃₇₄₁₄<br>BD₃₅₀₂₇B<br>990₃₃₂₃₉99H<br>5₃₀₆₀₆FEK||184502<br>178773<br>112025<br>108452<br>47336<br>45023<br>37415<br>35029<br>33244<br>30609||243952<br>236377<br>148121<br>143397<br>62588<br>59531<br>49471<br>46316<br>43956<br>40472||(47×21¹⁸⁴⁵⁰¹+953)/20<br>(309×21¹⁷⁸⁷⁷²+71)/20<br>(288×21¹¹²⁰²³−13)/5<br>(7×21¹⁰⁸⁴⁵²+4733)/20<br>4×21⁴⁷³³⁵+205<br>240×21⁴⁵⁰²¹+299<br>(353×21³⁷⁴¹⁴−13)/20<br>(233×21³⁵⁰²⁸−53)/20<br>198×21³³²⁴²+4175<br>(21³⁰⁶⁰⁹+18455)/4||http://factordb.com/index.php?id=1100000008700600990&open=prime<br>http://factordb.com/index.php?id=1100000008700596669&open=prime<br>http://factordb.com/index.php?id=1100000008700593358&open=prime<br>http://factordb.com/index.php?id=1100000008700586183&open=prime<br>http://factordb.com/index.php?id=1100000000808118331&open=prime<br>http://factordb.com/index.php?id=1100000003996110311&open=prime<br>http://factordb.com/index.php?id=1100000003996110479&open=prime<br>http://factordb.com/index.php?id=1100000003996110718&open=prime<br>http://factordb.com/index.php?id=1100000003996110944&open=prime<br>http://factordb.com/index.php?id=1100000003996111130&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000008700600990&base=21<br>http://factordb.com/index.php?showid=1100000008700596669&base=21<br>http://factordb.com/index.php?showid=1100000008700593358&base=21<br>http://factordb.com/index.php?showid=1100000008700586183&base=21<br>http://factordb.com/index.php?showid=1100000000808118331&base=21<br>http://factordb.com/index.php?showid=1100000003996110311&base=21<br>http://factordb.com/index.php?showid=1100000003996110479&base=21<br>http://factordb.com/index.php?showid=1100000003996110718&base=21<br>http://factordb.com/index.php?showid=1100000003996110944&base=21<br>http://factordb.com/index.php?showid=1100000003996111130&base=21<nowiki/>||8||200000|| |- ||22||8003||BK₂₂₀₀₁5<br>7₃₈₁₅2L<br>L₂₃₈₅KE7<br>7₉₅₉K7<br>J0₇₆₇IGGJ<br>K0₇₆₀EC1<br>I₆₂₆AF<br>E60₄₉₆L<br>L₄₈₃G3<br>L0₄₅₄B63||22003<br>3817<br>2388<br>961<br>772<br>764<br>628<br>499<br>485<br>458||29538<br>5124<br>3206<br>1290<br>1037<br>1026<br>843<br>670<br>652<br>615||(251×22²²⁰⁰²−335)/21<br>(22³⁸¹⁷−289)/3<br>22²³⁸⁸−653<br>(22⁹⁶¹+857)/3<br>19×22⁷⁷¹+199779<br>20×22⁷⁶³+7041<br>(6×22⁶²⁸−1259)/7<br>314×22⁴⁹⁷+21<br>22⁴⁸⁵−129<br>21×22⁴⁵⁷+5459||http://factordb.com/index.php?id=1100000003594696838&open=prime<br>http://factordb.com/index.php?id=1100000003591359839&open=prime<br>http://factordb.com/index.php?id=1100000003591360774&open=prime<br>http://factordb.com/index.php?id=1100000003591361817&open=prime<br>http://factordb.com/index.php?id=1100000003591362567&open=prime<br>http://factordb.com/index.php?id=1100000000632724415&open=prime<br>http://factordb.com/index.php?id=1100000000632724334&open=prime<br>http://factordb.com/index.php?id=1100000000632703239&open=prime<br>http://factordb.com/index.php?id=1100000003591364730&open=prime<br>http://factordb.com/index.php?id=1100000003591365331&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000003594696838&base=22<br>http://factordb.com/index.php?showid=1100000003591359839&base=22<br>http://factordb.com/index.php?showid=1100000003591360774&base=22<br>http://factordb.com/index.php?showid=1100000003591361817&base=22<br>http://factordb.com/index.php?showid=1100000003591362567&base=22<br>http://factordb.com/index.php?showid=1100000000632724415&base=22<br>http://factordb.com/index.php?showid=1100000000632724334&base=22<br>http://factordb.com/index.php?showid=1100000000632703239&base=22<br>http://factordb.com/index.php?showid=1100000003591364730&base=22<br>http://factordb.com/index.php?showid=1100000003591365331&base=22<nowiki/>||0||–|| |- ||23||65178~65265||B0₉₃₀₄₆FB<br>L₈₆₄₄₄D<br>AJ₈₁₀₆₅4<br>20₇₃₅₆₀98<br>J₆₈₂₁₇G4<br>D70₆₆₇₇₀B<br>5F₆₂₃₄₀6<br>A7M7₆₁₅₃₂<br>B30₆₁₁₃₆5<br>EJ₅₂₁₆₉||93049<br>86445<br>81067<br>73563<br>68219<br>66773<br>62342<br>61535<br>61139<br>52170||126708<br>117715<br>110391<br>100172<br>92896<br>90927<br>84893<br>83794<br>83255<br>71042||11×23⁹³⁰⁴⁸+356<br>(21×23⁸⁶⁴⁴⁵−197)/22<br>(239×23⁸¹⁰⁶⁶−349)/22<br>2×23⁷³⁵⁶²+215<br>(19×23⁶⁸²¹⁹−1867)/22<br>306×23⁶⁶⁷⁷¹+11<br>(125×23⁶²³⁴¹−213)/22<br>(120413×23⁶¹⁵³²−7)/22<br>256×23⁶¹¹³⁷+5<br>(327×23⁵²¹⁶⁹−19)/22||http://factordb.com/index.php?id=1100000004691540361&open=prime<br>http://factordb.com/index.php?id=1100000004691546739&open=prime<br>http://factordb.com/index.php?id=1100000004691548070&open=prime<br>http://factordb.com/index.php?id=1100000004691548569&open=prime<br>http://factordb.com/index.php?id=1100000004691549462&open=prime<br>http://factordb.com/index.php?id=1100000004691549803&open=prime<br>http://factordb.com/index.php?id=1100000004691551005&open=prime<br>http://factordb.com/index.php?id=1100000004691556967&open=prime<br>http://factordb.com/index.php?id=1100000004691557254&open=prime<br>http://factordb.com/index.php?id=1100000004691557548&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000004691540361&base=23<br>http://factordb.com/index.php?showid=1100000004691546739&base=23<br>http://factordb.com/index.php?showid=1100000004691548070&base=23<br>http://factordb.com/index.php?showid=1100000004691548569&base=23<br>http://factordb.com/index.php?showid=1100000004691549462&base=23<br>http://factordb.com/index.php?showid=1100000004691549803&base=23<br>http://factordb.com/index.php?showid=1100000004691551005&base=23<br>http://factordb.com/index.php?showid=1100000004691556967&base=23<br>http://factordb.com/index.php?showid=1100000004691557254&base=23<br>http://factordb.com/index.php?showid=1100000004691557548&base=23<nowiki/>||87||100000|| |- ||24||3409||N00N₈₁₂₉LN<br>88N₅₉₅₁<br>A0₂₉₅₁8ID<br>D₂₆₉₈LD<br>N₂₆₄₄LLN<br>BC0₃₃₁B<br>20₃₁₃7<br>C7₂₉₈<br>D0₂₅₉KKD<br>I0₂₄₁I5||8134<br>5953<br>2955<br>2700<br>2647<br>334<br>315<br>299<br>263<br>244||11227<br>8216<br>4079<br>3727<br>3654<br>461<br>434<br>413<br>363<br>337||13249×24⁸¹³¹−49<br>201×24⁵⁹⁵¹−1<br>10×24²⁹⁵⁴+5053<br>(13×24²⁷⁰⁰+4403)/23<br>24²⁶⁴⁷−1201<br>276×24³³²+11<br>2×24³¹⁴+7<br>(283×24²⁹⁸−7)/23<br>13×24²⁶²+12013<br>18×24²⁴³+437||http://factordb.com/index.php?id=1100000003593391606&open=prime<br>http://factordb.com/index.php?id=1100000003593275880&open=prime<br>http://factordb.com/index.php?id=1100000003593269654&open=prime<br>http://factordb.com/index.php?id=1100000003593269876&open=prime<br>http://factordb.com/index.php?id=1100000003593270089&open=prime<br>http://factordb.com/index.php?id=1100000002633359842&open=prime<br>http://factordb.com/index.php?id=1100000002355610241&open=prime<br>http://factordb.com/index.php?id=1100000002326181235&open=prime<br>http://factordb.com/index.php?id=1100000003593270725&open=prime<br>http://factordb.com/index.php?id=1100000002633360037&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000003593391606&base=24<br>http://factordb.com/index.php?showid=1100000003593275880&base=24<br>http://factordb.com/index.php?showid=1100000003593269654&base=24<br>http://factordb.com/index.php?showid=1100000003593269876&base=24<br>http://factordb.com/index.php?showid=1100000003593270089&base=24<br>http://factordb.com/index.php?showid=1100000002633359842&base=24<br>http://factordb.com/index.php?showid=1100000002355610241&base=24<br>http://factordb.com/index.php?showid=1100000002326181235&base=24<br>http://factordb.com/index.php?showid=1100000003593270725&base=24<br>http://factordb.com/index.php?showid=1100000002633360037&base=24<nowiki/>||0||–|| |- ||25||133639~133724||E₉₈₃₉₆FOO<br>1J710₉₆₂₇₂1<br>NB0₈₅₅₉₈5NH<br>D70₈₁₅₈₁JJ7<br>F0₈₀₀₅₄HL<br>J010₇₅₉₄₃E7<br>K₆₇₇₇₁5I<br>LO₆₆₃₇₇KC<br>KJD0₆₃₃₉₉1<br>70₆₀₈₉₂D711||98399<br>96277<br>85603<br>81586<br>80057<br>75948<br>67773<br>66380<br>63403<br>60897||137556<br>134589<br>119668<br>114053<br>111915<br>106171<br>94743<br>92796<br>88634<br>85130||(7×25⁹⁸³⁹⁹+10613)/12<br>27676×25⁹⁶²⁷³+1<br>586×25⁸⁵⁶⁰¹+3717<br>332×25⁸¹⁵⁸⁴+12357<br>15×25⁸⁰⁰⁵⁶+446<br>11876×25⁷⁵⁹⁴⁵+357<br>(5×25⁶⁷⁷⁷³−2267)/6<br>22×25⁶⁶³⁷⁹−113<br>12988×25⁶³⁴⁰⁰+1<br>7×25⁶⁰⁸⁹⁶+207526||http://factordb.com/index.php?id=1100000000808118215&open=prime<br>http://factordb.com/index.php?id=1100000003983674902&open=prime<br>http://factordb.com/index.php?id=1100000004909706420&open=prime<br>http://factordb.com/index.php?id=1100000004909733266&open=prime<br>http://factordb.com/index.php?id=1100000004909750102&open=prime<br>http://factordb.com/index.php?id=1100000004909770736&open=prime<br>http://factordb.com/index.php?id=1100000004586986394&open=prime<br>http://factordb.com/index.php?id=1100000000808118270&open=prime<br>http://factordb.com/index.php?id=1100000004586986664&open=prime<br>http://factordb.com/index.php?id=1100000004586986798&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000000808118215&base=25<br>http://factordb.com/index.php?showid=1100000003983674902&base=25<br>http://factordb.com/index.php?showid=1100000004909706420&base=25<br>http://factordb.com/index.php?showid=1100000004909733266&base=25<br>http://factordb.com/index.php?showid=1100000004909750102&base=25<br>http://factordb.com/index.php?showid=1100000004909770736&base=25<br>http://factordb.com/index.php?showid=1100000004586986394&base=25<br>http://factordb.com/index.php?showid=1100000000808118270&base=25<br>http://factordb.com/index.php?showid=1100000004586986664&base=25<br>http://factordb.com/index.php?showid=1100000004586986798&base=25<nowiki/>||85||100000|| |- ||26||25256~25259||85M₁₉₇₀₆₀B<br>M0₆₁₁₈₆2BB<br>J0₄₄₃₀₃KCB<br>6K₂₃₃₀₀5<br>LD0₂₀₉₇₅7<br>7₂₀₂₇₉OL<br>5₁₉₃₉₁6F<br>9GDK₁₅₉₂₀P<br>M₈₇₇₂P<br>K0₄₃₆₄I5||197063<br>61190<br>44307<br>23302<br>20978<br>20281<br>19393<br>15924<br>8773<br>4367||278839<br>86583<br>62694<br>32972<br>29684<br>28697<br>27440<br>22532<br>12414<br>6180||(5347×26¹⁹⁷⁰⁶¹−297)/25<br>22×26⁶¹¹⁸⁹+1649<br>19×26⁴⁴³⁰⁶+13843<br>(34×26²³³⁰¹−79)/5<br>559×26²⁰⁹⁷⁶+7<br>(7×26²⁰²⁸¹+11393)/25<br>(26¹⁹³⁹³+179)/5<br>(32569×26¹⁵⁹²¹+21)/5<br>(22×26⁸⁷⁷³+53)/25<br>20×26⁴³⁶⁶+473||http://factordb.com/index.php?id=1100000008573990023&open=prime<br>http://factordb.com/index.php?id=1100000003968169875&open=prime<br>http://factordb.com/index.php?id=1100000003968156595&open=prime<br>http://factordb.com/index.php?id=1100000003892628745&open=prime<br>http://factordb.com/index.php?id=1100000003892628658&open=prime<br>http://factordb.com/index.php?id=1100000003892628605&open=prime<br>http://factordb.com/index.php?id=1100000003850151202&open=prime<br>http://factordb.com/index.php?id=1100000003850155316&open=prime<br>http://factordb.com/index.php?id=1100000000758011195&open=prime<br>http://factordb.com/index.php?id=1100000002634136508&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000008573990023&base=26<br>http://factordb.com/index.php?showid=1100000003968169875&base=26<br>http://factordb.com/index.php?showid=1100000003968156595&base=26<br>http://factordb.com/index.php?showid=1100000003892628745&base=26<br>http://factordb.com/index.php?showid=1100000003892628658&base=26<br>http://factordb.com/index.php?showid=1100000003892628605&base=26<br>http://factordb.com/index.php?showid=1100000003850151202&base=26<br>http://factordb.com/index.php?showid=1100000003850155316&base=26<br>http://factordb.com/index.php?showid=1100000000758011195&base=26<br>http://factordb.com/index.php?showid=1100000002634136508&base=26<nowiki/>||3||200000|| |- ||27||102852~102896||CA0F₈₈₈₈₃A<br>GNN0₇₈₇₉₅N<br>O44L₆₆₀₁₆7<br>NJ0₆₄₃₆₉H<br>ME₄₉₆₄₀9G<br>PH0₄₇₈₉₀1<br>QF₄₇₁₆₅AF5<br>J0₄₀₇₉₁PD<br>510₃₉₁₆₄I07<br>NGN0₃₆₃₂₉N||88887<br>78799<br>66020<br>64372<br>49643<br>47893<br>47169<br>40794<br>39169<br>36333||127230<br>112790<br>94499<br>92140<br>71058<br>68553<br>67516<br>58391<br>56065<br>52006||(234483×27⁸⁸⁸⁸⁴−145)/26<br>12308×27⁷⁸⁷⁹⁶+23<br>(457829×27⁶⁶⁰¹⁷−385)/26<br>640×27⁶⁴³⁷⁰+17<br>(293×27⁴⁹⁶⁴²−1736)/13<br>692×27⁴⁷⁸⁹¹+1<br>(691×27⁴⁷¹⁶⁸−95045)/26<br>19×27⁴⁰⁷⁹³+688<br>136×27³⁹¹⁶⁷+13129<br>17222×27³⁶³³⁰+23||http://factordb.com/index.php?id=1100000000808118233&open=prime<br>http://factordb.com/index.php?id=1100000004681348398&open=prime<br>http://factordb.com/index.php?id=1100000004374140861&open=prime<br>http://factordb.com/index.php?id=1100000004374138999&open=prime<br>http://factordb.com/index.php?id=1100000000819229859&open=prime<br>http://factordb.com/index.php?id=1100000004102754118&open=prime<br>http://factordb.com/index.php?id=1100000004102755880&open=prime<br>http://factordb.com/index.php?id=1100000004102758254&open=prime<br>http://factordb.com/index.php?id=1100000004102875088&open=prime<br>http://factordb.com/index.php?id=1100000004103372866&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000000808118233&base=27<br>http://factordb.com/index.php?showid=1100000004681348398&base=27<br>http://factordb.com/index.php?showid=1100000004374140861&base=27<br>http://factordb.com/index.php?showid=1100000004374138999&base=27<br>http://factordb.com/index.php?showid=1100000000819229859&base=27<br>http://factordb.com/index.php?showid=1100000004102754118&base=27<br>http://factordb.com/index.php?showid=1100000004102755880&base=27<br>http://factordb.com/index.php?showid=1100000004102758254&base=27<br>http://factordb.com/index.php?showid=1100000004102875088&base=27<br>http://factordb.com/index.php?showid=1100000004103372866&base=27<nowiki/>||44||100000|| |- ||28||25528~25529||O4O₉₄₅₃₅9<br>5OA₃₁₂₃₈F<br>N6₂₄₀₅₁LR<br>D0₅₂₆₇77D<br>QO₄₂₃₉69<br>5₃₇₄₆8P<br>G0₁₈₉₉AN<br>A₁₄₂₃6F<br>5I₁₃₇₀F<br>5₁₃₃₂P8P||94538<br>31241<br>24054<br>5271<br>4242<br>3748<br>1902<br>1425<br>1372<br>1335||136812<br>45210<br>34810<br>7628<br>6139<br>5424<br>2753<br>2062<br>1985<br>1932||(6092×28⁹⁴⁵³⁶−143)/9<br>(4438×28³¹²³⁹+125)/27<br>(209×28²⁴⁰⁵³+3967)/9<br>13×28⁵²⁷⁰+5697<br>(242×28⁴²⁴¹−4679)/9<br>(5×28³⁷⁴⁸+2803)/27<br>16×28¹⁹⁰¹+303<br>(10×28¹⁴²⁵−2899)/27<br>(17×28¹³⁷¹−11)/3<br>(5×28¹³³⁵+426163)/27||http://factordb.com/index.php?id=1100000000808118231&open=prime<br>http://factordb.com/index.php?id=1100000003880455200&open=prime<br>http://factordb.com/index.php?id=1100000003879667576&open=prime<br>http://factordb.com/index.php?id=1100000003850151420&open=prime<br>http://factordb.com/index.php?id=1100000000840839934&open=prime<br>http://factordb.com/index.php?id=1100000003850161974&open=prime<br>http://factordb.com/index.php?id=1100000003850161973&open=prime<br>http://factordb.com/index.php?id=1100000000840839947&open=prime<br>http://factordb.com/index.php?id=1100000003850161972&open=prime<br>http://factordb.com/index.php?id=1100000003850161965&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000000808118231&base=28<br>http://factordb.com/index.php?showid=1100000003880455200&base=28<br>http://factordb.com/index.php?showid=1100000003879667576&base=28<br>http://factordb.com/index.php?showid=1100000003850151420&base=28<br>http://factordb.com/index.php?showid=1100000000840839934&base=28<br>http://factordb.com/index.php?showid=1100000003850161974&base=28<br>http://factordb.com/index.php?showid=1100000003850161973&base=28<br>http://factordb.com/index.php?showid=1100000000840839947&base=28<br>http://factordb.com/index.php?showid=1100000003850161972&base=28<br>http://factordb.com/index.php?showid=1100000003850161965&base=28<nowiki/>||1||900000|| |- ||29||355242~355367||830₉₉₃₇₇4<br>GP5J₉₄₉₃₅<br>P05J₉₀₂₈₉<br>BBD0₈₈₈₈₈PB<br>8B₈₅₃₃₃G<br>L0₈₁₅₇₁5955<br>E0₇₇₃₇₂L7B<br>LPC₇₅₁₅₁9<br>JR0₇₄₆₂₂7<br>B₇₄₅₀₁0RP||99380<br>94938<br>90292<br>88893<br>85335<br>81576<br>77376<br>75154<br>74625<br>74504||145333<br>138837<br>132043<br>129997<br>124794<br>119297<br>113155<br>109905<br>109132<br>108955||235×29⁹⁹³⁷⁸+4<br>(397227×29⁹⁴⁹³⁵−19)/28<br>(588859×29⁹⁰²⁸⁹−19)/28<br>9583×29⁸⁸⁸⁹⁰+736<br>(235×29⁸⁵³³⁴+129)/14<br>21×29⁸¹⁵⁷⁵+129664<br>14×29⁷⁷³⁷⁵+17875<br>(4441×29⁷⁵¹⁵²−24)/7<br>578×29⁷⁴⁶²³+7<br>(11×29⁷⁴⁵⁰⁴−245655)/28||http://factordb.com/index.php?id=1100000008253882372&open=prime<br>http://factordb.com/index.php?id=1100000008253893542&open=prime<br>http://factordb.com/index.php?id=1100000008253899083&open=prime<br>http://factordb.com/index.php?id=1100000008253909183&open=prime<br>http://factordb.com/index.php?id=1100000008253921388&open=prime<br>http://factordb.com/index.php?id=1100000008253925955&open=prime<br>http://factordb.com/index.php?id=1100000008253931446&open=prime<br>http://factordb.com/index.php?id=1100000000808118236&open=prime<br>http://factordb.com/index.php?id=1100000008253934219&open=prime<br>http://factordb.com/index.php?id=1100000008253936120&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000008253882372&base=29<br>http://factordb.com/index.php?showid=1100000008253893542&base=29<br>http://factordb.com/index.php?showid=1100000008253899083&base=29<br>http://factordb.com/index.php?showid=1100000008253909183&base=29<br>http://factordb.com/index.php?showid=1100000008253921388&base=29<br>http://factordb.com/index.php?showid=1100000008253925955&base=29<br>http://factordb.com/index.php?showid=1100000008253931446&base=29<br>http://factordb.com/index.php?showid=1100000000808118236&base=29<br>http://factordb.com/index.php?showid=1100000008253934219&base=29<br>http://factordb.com/index.php?showid=1100000008253936120&base=29<nowiki/>||125||100000|| |- ||30||2619||OT₃₄₂₀₅<br>I0₂₄₆₀₈D<br>5₄₈₈₂J<br>C0₁₀₂₂1<br>M0₅₄₇SS7<br>M₂₄₁QB<br>AN₂₀₆<br>50₁₆₄B<br>J₁₅₃QJ<br>J₉₄QQJ||34206<br>24610<br>4883<br>1024<br>551<br>243<br>207<br>166<br>155<br>97||50527<br>36352<br>7213<br>1513<br>814<br>359<br>306<br>245<br>229<br>144||25×30³⁴²⁰⁵−1<br>18×30²⁴⁶⁰⁹+13<br>(5×30⁴⁸⁸³+401)/29<br>12×30¹⁰²³+1<br>22×30⁵⁵⁰+26047<br>(22×30²⁴³+3139)/29<br>(313×30²⁰⁶−23)/29<br>5×30¹⁶⁵+11<br>(19×30¹⁵⁵+6071)/29<br>(19×30⁹⁷+188771)/29||http://factordb.com/index.php?id=1100000000800812865&open=prime<br>http://factordb.com/index.php?id=1100000003593967511&open=prime<br>http://factordb.com/index.php?id=1100000002327649423&open=prime<br>http://factordb.com/index.php?id=1100000000785448736&open=prime<br>http://factordb.com/index.php?id=1100000003593407988&open=prime<br>http://factordb.com/index.php?id=1100000003593408295&open=prime<br>http://factordb.com/index.php?id=1100000002327651073&open=prime<br>http://factordb.com/index.php?id=1100000002356282476&open=ecm<br>http://factordb.com/index.php?id=1100000003593409109&open=ecm<br>http://factordb.com/index.php?id=1100000003593409165&open=ecm<nowiki/>||http://factordb.com/index.php?showid=1100000000800812865&base=30<br>http://factordb.com/index.php?showid=1100000003593967511&base=30<br>http://factordb.com/index.php?showid=1100000002327649423&base=30<br>http://factordb.com/index.php?showid=1100000000785448736&base=30<br>http://factordb.com/index.php?showid=1100000003593407988&base=30<br>http://factordb.com/index.php?showid=1100000003593408295&base=30<br>http://factordb.com/index.php?showid=1100000002327651073&base=30<br>http://factordb.com/index.php?showid=1100000002356282476&base=30<br>http://factordb.com/index.php?showid=1100000003593409109&base=30<br>http://factordb.com/index.php?showid=1100000003593409165&base=30<nowiki/>||0||–|| |- ||31||569323~569400||2IIF₉₁₈₀₅<br>B0₈₈₃₀₉APO9<br>J0T₇₇₅₁₆<br>J090₇₇₁₂₈NNN<br>D₆₉₈₆₁QO<br>9MH0₆₈₆₃₇D<br>J₆₇₁₆₂D<br>N0₆₆₉₇₁32P<br>DDDQ0₆₄₀₈₈TD<br>U₆₃₈₆₁CM3||91808<br>88314<br>77518<br>77134<br>69863<br>68641<br>67163<br>66975<br>64094<br>63864||136918<br>131708<br>115608<br>115035<br>104191<br>102369<br>100165<br>99884<br>95587<br>95245||(4997×31⁹¹⁸⁰⁵−1)/2<br>11×31⁸⁸³¹³+322688<br>(17699×31⁷⁷⁵¹⁶−29)/30<br>18268×31⁷⁷¹³¹+22839<br>(13×31⁶⁹⁸⁶³+12407)/30<br>9348×31⁶⁸⁶³⁸+13<br>(19×31⁶⁷¹⁶³−199)/30<br>23×31⁶⁶⁹⁷⁴+2970<br>400205×31⁶⁴⁰⁹⁰+912<br>31⁶³⁸⁶⁴−17574||http://factordb.com/index.php?id=1100000007050395732&open=prime<br>http://factordb.com/index.php?id=1100000007050397309&open=prime<br>http://factordb.com/index.php?id=1100000007050398940&open=prime<br>http://factordb.com/index.php?id=1100000007050400178&open=prime<br>http://factordb.com/index.php?id=1100000006965878559&open=prime<br>http://factordb.com/index.php?id=1100000006965875678&open=prime<br>http://factordb.com/index.php?id=1100000006965873668&open=prime<br>http://factordb.com/index.php?id=1100000006965870538&open=prime<br>http://factordb.com/index.php?id=1100000006965868103&open=prime<br>http://factordb.com/index.php?id=1100000006965865343&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000007050395732&base=31<br>http://factordb.com/index.php?showid=1100000007050397309&base=31<br>http://factordb.com/index.php?showid=1100000007050398940&base=31<br>http://factordb.com/index.php?showid=1100000007050400178&base=31<br>http://factordb.com/index.php?showid=1100000006965878559&base=31<br>http://factordb.com/index.php?showid=1100000006965875678&base=31<br>http://factordb.com/index.php?showid=1100000006965873668&base=31<br>http://factordb.com/index.php?showid=1100000006965870538&base=31<br>http://factordb.com/index.php?showid=1100000006965868103&base=31<br>http://factordb.com/index.php?showid=1100000006965865343&base=31<nowiki/>||77||100000|| |- ||32||168882~169002||V₉₉₅₈₃63<br>6₈₉₀₇₄AF<br>8₇₇₇₀₀H<br>Q₇₇₄₀₁EQQQ3<br>8₇₇₂₄₉3<br>JM₇₆₀₂₈L<br>E₇₂₉₁₉IL<br>B0₆₇₆₈₀CB<br>GK₆₆₀₇₆F<br>KN₆₅₀₂₂||99585<br>89076<br>77701<br>77406<br>77250<br>76030<br>72921<br>67683<br>66078<br>65023||149891<br>134073<br>116952<br>116508<br>116273<br>114437<br>109757<br>101873<br>99458<br>97870||32⁹⁹⁵⁸⁵−829<br>(6×32⁸⁹⁰⁷⁶+4241)/31<br>(8×32⁷⁷⁷⁰¹+271)/31<br>(26×32⁷⁷⁴⁰⁶−390071011)/31<br>(8×32⁷⁷²⁵⁰−163)/31<br>(611×32⁷⁶⁰²⁹−53)/31<br>(14×32⁷²⁹²¹+4171)/31<br>11×32⁶⁷⁶⁸²+395<br>(516×32⁶⁶⁰⁷⁷−175)/31<br>(643×32⁶⁵⁰²²−23)/31||http://factordb.com/index.php?id=1100000005514892191&open=prime<br>http://factordb.com/index.php?id=1100000005514897129&open=prime<br>http://factordb.com/index.php?id=1100000005514901700&open=prime<br>http://factordb.com/index.php?id=1100000005514915338&open=prime<br>http://factordb.com/index.php?id=1100000005514918574&open=prime<br>http://factordb.com/index.php?id=1100000005514922523&open=prime<br>http://factordb.com/index.php?id=1100000004591654373&open=prime<br>http://factordb.com/index.php?id=1100000004591654467&open=prime<br>http://factordb.com/index.php?id=1100000004591654632&open=prime<br>http://factordb.com/index.php?id=1100000004591654952&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000005514892191&base=32<br>http://factordb.com/index.php?showid=1100000005514897129&base=32<br>http://factordb.com/index.php?showid=1100000005514901700&base=32<br>http://factordb.com/index.php?showid=1100000005514915338&base=32<br>http://factordb.com/index.php?showid=1100000005514918574&base=32<br>http://factordb.com/index.php?showid=1100000005514922523&base=32<br>http://factordb.com/index.php?showid=1100000004591654373&base=32<br>http://factordb.com/index.php?showid=1100000004591654467&base=32<br>http://factordb.com/index.php?showid=1100000004591654632&base=32<br>http://factordb.com/index.php?showid=1100000004591654952&base=32<nowiki/>||120||100000|| |- ||33||280012~280093||DP₉₅₀₉₃M5<br>HJ0₉₄₂₉₅J<br>90₉₃₅₉₇Q<br>9F0₉₃₁₅₇N<br>7₈₉₄₄₉333H<br>K3₈₀₇₅₁6K<br>D₈₀₁₀₇9UD<br>VFU₇₂₂₀₄FK<br>J₆₈₇₁₅2BJ<br>DF0₆₈₃₆₇J||95096<br>94298<br>93599<br>93160<br>89453<br>80754<br>80110<br>72208<br>68718<br>68370||144405<br>143193<br>142131<br>141465<br>135835<br>122626<br>121648<br>109649<br>104350<br>103821||(441×33⁹⁵⁰⁹⁵−3833)/32<br>580×33⁹⁴²⁹⁶+19<br>9×33⁹³⁵⁹⁸+26<br>312×33⁹³¹⁵⁸+23<br>(7×33⁸⁹⁴⁵³−4743239)/32<br>(643×33⁸⁰⁷⁵³+3709)/32<br>(13×33⁸⁰¹¹⁰−121453)/32<br>(16623×33⁷²²⁰⁶−8095)/16<br>(19×33⁶⁸⁷¹⁸−600883)/32<br>444×33⁶⁸³⁶⁸+19||http://factordb.com/index.php?id=1100000005652348775&open=prime<br>http://factordb.com/index.php?id=1100000005652362811&open=prime<br>http://factordb.com/index.php?id=1100000005652375073&open=prime<br>http://factordb.com/index.php?id=1100000005652389776&open=prime<br>http://factordb.com/index.php?id=1100000005652430746&open=prime<br>http://factordb.com/index.php?id=1100000005652446200&open=prime<br>http://factordb.com/index.php?id=1100000005652461592&open=prime<br>http://factordb.com/index.php?id=1100000004614764298&open=prime<br>http://factordb.com/index.php?id=1100000004614770536&open=prime<br>http://factordb.com/index.php?id=1100000004614784274&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000005652348775&base=33<br>http://factordb.com/index.php?showid=1100000005652362811&base=33<br>http://factordb.com/index.php?showid=1100000005652375073&base=33<br>http://factordb.com/index.php?showid=1100000005652389776&base=33<br>http://factordb.com/index.php?showid=1100000005652430746&base=33<br>http://factordb.com/index.php?showid=1100000005652446200&base=33<br>http://factordb.com/index.php?showid=1100000005652461592&base=33<br>http://factordb.com/index.php?showid=1100000004614764298&base=33<br>http://factordb.com/index.php?showid=1100000004614770536&base=33<br>http://factordb.com/index.php?showid=1100000004614784274&base=33<nowiki/>||81||100000|| |- ||34||184785~184832||GFGC₉₉₉₉₆5<br>90₉₇₉₅₀FJ<br>NM0₈₅₂₁₈KX<br>F₈₃₁₈₉H2HP<br>P₇₉₄₄₁444P<br>6₇₇₀₂₇8X<br>XQIQ₇₂₂₄₁D<br>T₆₆₅₃₀IF<br>4₆₆₁₅₂B<br>2EEC₆₆₀₃₉7||100000<br>97953<br>85222<br>83193<br>79445<br>77029<br>72245<br>66532<br>66153<br>66043||153148<br>150013<br>130516<br>127408<br>121669<br>117968<br>110642<br>101893<br>101312<br>101143||(209246×34⁹⁹⁹⁹⁷−81)/11<br>9×34⁹⁷⁹⁵²+529<br>804×34⁸⁵²²⁰+713<br>(5×34⁸³¹⁹³+700233)/11<br>(25×34⁷⁹⁴⁴⁵−28062367)/33<br>(2×34⁷⁷⁰²⁹+1043)/11<br>(1288676×34⁷²²⁴²−455)/33<br>(29×34⁶⁶⁵³²−12833)/33<br>(4×34⁶⁶¹⁵³+227)/33<br>(30826×34⁶⁶⁰⁴⁰−59)/11||http://factordb.com/index.php?id=1100000004702891268&open=prime<br>http://factordb.com/index.php?id=1100000004702894713&open=prime<br>http://factordb.com/index.php?id=1100000004702900996&open=prime<br>http://factordb.com/index.php?id=1100000004702910376&open=prime<br>http://factordb.com/index.php?id=1100000004702913746&open=prime<br>http://factordb.com/index.php?id=1100000004702918600&open=prime<br>http://factordb.com/index.php?id=1100000004399656529&open=prime<br>http://factordb.com/index.php?id=1100000004399657696&open=prime<br>http://factordb.com/index.php?id=1100000004399658651&open=prime<br>http://factordb.com/index.php?id=1100000004399659716&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000004702891268&base=34<br>http://factordb.com/index.php?showid=1100000004702894713&base=34<br>http://factordb.com/index.php?showid=1100000004702900996&base=34<br>http://factordb.com/index.php?showid=1100000004702910376&base=34<br>http://factordb.com/index.php?showid=1100000004702913746&base=34<br>http://factordb.com/index.php?showid=1100000004702918600&base=34<br>http://factordb.com/index.php?showid=1100000004399656529&base=34<br>http://factordb.com/index.php?showid=1100000004399657696&base=34<br>http://factordb.com/index.php?showid=1100000004399658651&base=34<br>http://factordb.com/index.php?showid=1100000004399659716&base=34<nowiki/>||47||100000|| |- ||35||720002~720062||N0N₉₉₉₇₁9<br>V0₈₃₆₆₉E73<br>N₈₁₅₆₃K7N<br>BJ0₈₁₂₇₉N<br>J0₈₀₀₆₂FUH<br>43V₇₉₇₅₄<br>9₇₆₆₀₀K3<br>LB₇₁₃₆₆PB<br>Q₆₄₁₅₀H<br>50₆₃₃₉₇5R||99974<br>83673<br>81566<br>81282<br>80066<br>79756<br>76602<br>71369<br>64151<br>63400||154367<br>129197<br>125944<br>125505<br>123628<br>123148<br>118279<br>110199<br>99054<br>97894||(27393×35⁹⁹⁹⁷²−499)/34<br>31×35⁸³⁶⁷²+17398<br>(23×35⁸¹⁵⁶⁶−144013)/34<br>404×35⁸¹²⁸⁰+23<br>19×35⁸⁰⁰⁶⁵+19442<br>(4893×35⁷⁹⁷⁵⁴−31)/34<br>(9×35⁷⁶⁶⁰²+12877)/34<br>(725×35⁷¹³⁶⁸+16649)/34<br>(13×35⁶⁴¹⁵¹−166)/17<br>5×35⁶³³⁹⁹+202||http://factordb.com/index.php?id=1100000008248342445&open=prime<br>http://factordb.com/index.php?id=1100000008248353306&open=prime<br>http://factordb.com/index.php?id=1100000008248375642&open=prime<br>http://factordb.com/index.php?id=1100000008248397018&open=prime<br>http://factordb.com/index.php?id=1100000008248412468&open=prime<br>http://factordb.com/index.php?id=1100000008248418540&open=prime<br>http://factordb.com/index.php?id=1100000008248423670&open=prime<br>http://factordb.com/index.php?id=1100000008192119974&open=prime<br>http://factordb.com/index.php?id=1100000008192126630&open=prime<br>http://factordb.com/index.php?id=1100000008192129294&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000008248342445&base=35<br>http://factordb.com/index.php?showid=1100000008248353306&base=35<br>http://factordb.com/index.php?showid=1100000008248375642&base=35<br>http://factordb.com/index.php?showid=1100000008248397018&base=35<br>http://factordb.com/index.php?showid=1100000008248412468&base=35<br>http://factordb.com/index.php?showid=1100000008248418540&base=35<br>http://factordb.com/index.php?showid=1100000008248423670&base=35<br>http://factordb.com/index.php?showid=1100000008192119974&base=35<br>http://factordb.com/index.php?showid=1100000008192126630&base=35<br>http://factordb.com/index.php?showid=1100000008192129294&base=35<nowiki/>||60||100000|| |- ||36||35286~35290||P₈₁₉₉₃SZ<br>S0₇₅₀₀₇8H<br>7K₂₆₅₆₇Z<br>J₁₀₁₁₇LJ<br>VL0₇₂₅₈J<br>EO0₆₁₇₇V<br>FZ₅₇₇₇3P<br>T09₄₆₁₈1<br>RY₄₅₆₂H<br>OZ₃₉₃₂AZ||81995<br>75010<br>26569<br>10119<br>7261<br>6180<br>5780<br>4621<br>4564<br>3935||127609<br>116739<br>41349<br>15748<br>11301<br>9618<br>8996<br>7192<br>7103<br>6124||(5×36⁸¹⁹⁹⁵+821)/7<br>28×36⁷⁵⁰⁰⁹+305<br>(53×36²⁶⁵⁶⁸+101)/7<br>(19×36¹⁰¹¹⁹+2501)/35<br>1137×36⁷²⁵⁹+19<br>528×36⁶¹⁷⁸+31<br>16×36⁵⁷⁷⁹−1163<br>(36549×36⁴⁶¹⁹−289)/35<br>(979×36⁴⁵⁶³−629)/35<br>25×36³⁹³⁴−901||http://factordb.com/index.php?id=1100000002394962083&open=prime<br>http://factordb.com/index.php?id=1100000004020085177&open=prime<br>http://factordb.com/index.php?id=1100000003896952461&open=prime<br>http://factordb.com/index.php?id=1100000003807362491&open=prime<br>http://factordb.com/index.php?id=1100000003807362489&open=prime<br>http://factordb.com/index.php?id=1100000003807362488&open=prime<br>http://factordb.com/index.php?id=1100000003807362487&open=prime<br>http://factordb.com/index.php?id=1100000003807362486&open=prime<br>http://factordb.com/index.php?id=1100000003807362485&open=prime<br>http://factordb.com/index.php?id=1100000000840634476&open=prime<nowiki/>||http://factordb.com/index.php?showid=1100000002394962083&base=36<br>http://factordb.com/index.php?showid=1100000004020085177&base=36<br>http://factordb.com/index.php?showid=1100000003896952461&base=36<br>http://factordb.com/index.php?showid=1100000003807362491&base=36<br>http://factordb.com/index.php?showid=1100000003807362489&base=36<br>http://factordb.com/index.php?showid=1100000003807362488&base=36<br>http://factordb.com/index.php?showid=1100000003807362487&base=36<br>http://factordb.com/index.php?showid=1100000003807362486&base=36<br>http://factordb.com/index.php?showid=1100000003807362485&base=36<br>http://factordb.com/index.php?showid=1100000000840634476&base=36<nowiki/>||4||200000|| |} == The fully proof of Athena problem in decimal (base ''b'' = 10) == '''Bold''' for the Athena primes, ''x'' ◁ ''y'' means ''x'' is a subsequence of ''y''. Assume ''p'' is a prime > 10, and the last digit of ''p'' must lie in {1,3,7,9}. Case 1: ''p'' ends with 1. In this case we can write ''p'' = ''x''1. If ''x'' contains 1, 3, 4, 6, or 7, then (respectively) '''11''' ◁ ''p'', '''31''' ◁ ''p'', '''41''' ◁ ''p'', '''61''' ◁ ''p'', or '''71''' ◁ ''p''. Hence we may assume all digits of ''x'' are 0, 2, 5, 8, or 9. Case 1.1: ''p'' begins with 2. In this case we can write ''p'' = 2''y''1. If 5 ◁ ''y'', then '''251''' ◁ ''p''. If 8 ◁ ''y'', then '''281''' ◁ ''p''. If 9 ◁ ''y'', then 29 ◁ ''p''. Hence we may assume all digits of ''y'' are 0 or 2. If 22 ◁ ''y'', then '''2221''' ◁ ''p''. Hence we may assume ''y'' contains zero or one 2's. If ''y'' contains no 2's, then ''p'' ∈ 2{0}1. But then, since the sum of the digits of ''p'' is 3, ''p'' is divisible by 3, so ''p'' cannot be prime. If ''y'' contains exactly one 2, then we can write ''p'' = 2''z''2''w''1, where ''z'',''w'' ∈ {0}. If 0 ◁ ''z'' and 0 ◁ ''w'', then '''20201''' ◁ ''p''. Hence we may assume either ''z'' or ''w'' is empty. If ''z'' is empty, then ''p'' ∈ 22{0}1, and the smallest prime ''p'' ∈ 22{0}1 is '''22000001'''. If ''w'' is empty, then ''p'' ∈ 2{0}21, and the smallest prime ''p'' ∈ 2{0}21 is '''20021'''. Case 1.2: ''p'' begins with 5. In this case we can write ''p'' = 5''y''1. If 2 ◁ ''y'', then '''521''' ◁ ''p''. If 9 ◁ ''y'', then 59 ◁ ''p''. Hence we may assume all digits of ''y'' are 0, 5, or 8. If 05 ◁ ''y'', then '''5051''' ◁ ''p''. If 08 ◁ ''y'', then '''5081''' ◁ ''p''. If 50 ◁ ''y'', then '''5501''' ◁ ''p''. If 58 ◁ ''y'', then '''5581''' ◁ ''p''. If 80 ◁ ''y'', then '''5801''' ◁ ''p''. If 85 ◁ ''y'', then '''5851''' ◁ ''p''. Hence we may assume ''y'' ∈ {0} ∪ {5} ∪ {8}. If ''y'' ∈ {0}, then ''p'' ∈ 5{0}1. But then, since the sum of the digits of ''p'' is 6, ''p'' is divisible by 3, so ''p'' cannot be prime. If ''y'' ∈ {5}, then ''p'' ∈ 5{5}1, and the smallest prime ''p'' ∈ 5{5}1 is '''555555555551'''. If ''y'' ∈ {8}, since if 88 ◁ ''y'', then 881 ◁ ''p'', hence we may assume ''y'' ∈ {''𝜆'',8}, and thus ''p'' ∈ {51,581}, but 51 and 581 are both composite. Case 1.3: ''p'' begins with 8. In this case we can write p = 8''y''1. If 2 ◁ ''y'', then '''821''' ◁ ''p''. If 8 ◁ ''y'', then '''881''' ◁ ''p''. If 9 ◁ ''y'', then 89 ◁ ''p''. Hence we may assume all digits of ''y'' are 0 or 5. If 50 ◁ ''y'', then '''8501''' ◁ ''p''. Hence we may assume y ∈ {0}{5}. If 005 ◁ ''y'', then '''80051''' ◁ p. Hence we may assume y ∈ {0} ∪ {5} ∪ 0{5}. If y ∈ {0}, then ''p'' ∈ 8{0}1. But then, since the sum of the digits of ''p'' is 9, ''p'' is divisible by 3, so ''p'' cannot be prime. If y ∈ {5}, since if 55555555555 ◁ ''y'', then 555555555551 ◁ ''p'', hence we may assume ''y'' ∈ {''𝜆'', 5, 55, 555, 5555, 55555, 555555, 5555555, 55555555, 555555555, 5555555555}, and thus ''p'' ∈ {81, 851, 8551, 85551, 855551, 8555551, 85555551, 855555551, 8555555551, 85555555551, 855555555551}, but all of these numbers are composite. If y ∈ 0{5}, since if 55555555555 ◁ ''y'', then 555555555551 ◁ ''p'', hence we may assume ''y'' ∈ {0, 05, 055, 0555, 05555, 055555, 0555555, 05555555, 055555555, 0555555555, 05555555555}, and thus ''p'' ∈ {801, 8051, 80551, 805551, 8055551, 80555551, 805555551, 8055555551, 80555555551, 805555555551, 8055555555551}, and of these numbers only 80555551 and 8055555551 are primes, but 80555551 ◁ 8055555551, thus only '''80555551''' is a minimal element. Case 1.4: ''p'' begins with 9. In this case we can write p = 9''y''1. If 9 ◁ ''y'', then '''991''' ◁ ''p''. Hence we may assume all digits of ''y'' are 0, 2, 5, or 8. If 00 ◁ ''y'', then '''9001''' ◁ ''p''. If 22 ◁ ''y'', then '''9221''' ◁ ''p''. If 55 ◁ ''y'', then '''9551''' ◁ ''p''. If 88 ◁ ''y'', then 881 ◁ ''p''. Hence we may assume ''y'' contains at most one 0, at most one 2, at most one 5, and at most one 8. If ''y'' only contains at most one 0 and does not contain any of {2,5,8}, then ''y'' ∈ {''𝜆'',0}, and thus ''p'' ∈ {91,901}, but 91 and 901 are both composite. If ''y'' only contains at most one 0 and only one of {2,5,8}, then the sum of the digits of ''p'' is divisible by 3, ''p'' is divisible by 3, so ''p'' cannot be prime. Hence we may assume ''y'' contains at least two of {2,5,8}. If 25 ◁ ''y'', then 251 ◁ ''p''. If 28 ◁ ''y'', then 281 ◁ ''p''. If 52 ◁ ''y'', then 521 ◁ ''p''. If 82 ◁ ''y'', then 821 ◁ ''p''. Hence we may assume ''y'' contains no 2's (since if ''y'' contains 2, then ''y'' cannot contain either 5's or 8's, which is a contradiction). If 85 ◁ ''y'', then '''9851''' ◁ ''p''. Hence we may assume ''y'' ∈ {58,580,508,058}, and thus ''p'' ∈ {9581,95801,95081,90581}, and of these numbers only 95801 is prime, but 95801 is not a minimal element since 5801 ◁ 95801. Case 2: ''p'' ends with 3. In this case we can write p = ''x''3. If ''x'' contains 1, 2, 4, 5, 7, or 8, then (respectively) '''13''' ◁ ''p'', '''23''' ◁ ''p'', '''43''' ◁ ''p'', '''53''' ◁ ''p'', '''73''' ◁ ''p'', or '''83''' ◁ ''p''. Hence we may assume all digits of ''x'' are 0, 3, 6, or 9, and thus all digits of ''p'' are 0, 3, 6, or 9. But then, since the digits of ''p'' all have a common factor 3, ''p'' is divisible by 3, so ''p'' cannot be prime. Case 3: ''p'' ends with 7. In this case we can write ''p'' = ''x''7. If ''x'' contains 1, 3, 4, 6, or 9, then (respectively) '''17''' ◁ ''p'', '''37''' ◁ ''p'', '''47''' ◁ ''p'', '''67''' ◁ ''p'', or '''97''' ◁ ''p''. Hence we may assume all digits of ''x'' are 0, 2, 5, 7, or 8. Case 3.1: ''p'' begins with 2. In this case we can write ''p'' = 2''y''7. If 2 ◁ ''y'', then '''227''' ◁ ''p''. If 5 ◁ ''y'', then '''257''' ◁ ''p''. If 7 ◁ ''y'', then '''277''' ◁ ''p''. Hence we may assume all digits of ''y'' are 0 or 8. If 08 ◁ ''y'', then '''2087''' ◁ ''p''. If 88 ◁ ''y'', then 887 ◁ ''p''. Hence we may assume ''y'' ∈ {0} ∪ 8{0}. If ''y'' ∈ {0}, then ''p'' ∈ 2{0}7. But then, since the sum of the digits of ''p'' is 9, ''p'' is divisible by 3, so ''p'' cannot be prime. If y ∈ 8{0}, then ''p'' ∈ 28{0}7. But then ''p'' is divisible by 7, since for ''n'' ≥ 0 we have 7 × 40_''n''1 = 280_''n''7. Case 3.2: ''p'' begins with 5. In this case we can write ''p'' = 5''y''7. If 5 ◁ ''y'', then '''557''' ◁ ''p''. If 7 ◁ ''y'', then '''577''' ◁ ''p''. If 8 ◁ ''y'', then '''587''' ◁ ''p''. Hence we may assume all digits of ''y'' are 0 or 2. If 22 ◁ ''y'', then 227 ◁ ''p''. Hence we may assume ''y'' contains zero or one 2's. If ''y'' contains no 2's, then ''p'' ∈ 5{0}7. But then, since the sum of the digits of ''p'' is 12, ''p'' is divisible by 3, so ''p'' cannot be prime. If ''y'' contains exactly one 2, then we can write ''p'' = 5''z''2''w''7, where ''z'',''w'' ∈ {0}. If 0 ◁ ''z'' and 0 ◁ ''w'', then '''50207''' ◁ ''p''. Hence we may assume either ''z'' or ''w'' is empty. If ''z'' is empty, then ''p'' ∈ 52{0}7, and the smallest prime ''p'' ∈ 52{0}7 is '''5200007'''. If ''w'' is empty, then ''p'' ∈ 5{0}27, and the smallest prime ''p'' ∈ 5{0}27 is '''5000000000000000000000000000027'''. Case 3.3: ''p'' begins with 7. In this case we can write ''p'' = 7''y''7. If 2 ◁ ''y'', then '''727''' ◁ ''p''. If 5 ◁ ''y'', then '''757''' ◁ ''p''. If 8 ◁ ''y'', then '''787''' ◁ ''p''. Hence we may assume all digits of ''y'' are 0 or 7, and thus all digits of ''p'' are 0 or 7. But then, since the digits of ''p'' all have a common factor 7, ''p'' is divisible by 7, so ''p'' cannot be prime. Case 3.4: ''p'' begins with 8. In this case we can write ''p'' = 8''y''7. If 2 ◁ ''y'', then '''827''' ◁ ''p''. If 5 ◁ ''y'', then '''857''' ◁ ''p''. If 7 ◁ ''y'', then '''877''' ◁ ''p''. If 8 ◁ ''y'', then '''887''' ◁ ''p''. Hence we may assume ''y'' ∈ {0}, and thus ''p'' ∈ 8{0}7. But then, since the sum of the digits of ''p'' is 15, ''p'' is divisible by 3, so ''p'' cannot be prime. Case 4: ''p'' ends with 9. In this case we can write ''p'' = ''x''9. If ''x'' contains 1, 2, 5, 7, or 8, then (respectively) '''19''' ◁ ''p'', '''29''' ◁ ''p'', '''59''' ◁ ''p'', '''79''' ◁ ''p'', or '''89''' ◁ ''p''. Hence we may assume all digits of ''x'' are 0, 3, 4, 6, or 9. If 44 ◁ ''x'', then '''449''' ◁ ''p''. Hence we may assume ''x'' contains zero or one 4's. If x contains no 4's, then all digits of ''x'' are 0, 3, 6, or 9, and thus all digits of ''p'' are 0, 3, 6, or 9. But then, since the digits of ''p'' all have a common factor 3, ''p'' is divisible by 3, so ''p'' cannot be prime. Hence we may assume that ''x'' contains exactly one 4. Case 4.1: ''p'' begins with 3. In this case we can write ''p'' = 3''y''4''z''9, where all digits of ''y'', ''z'' are 0, 3, 6, or 9. We must have '''349''' ◁ ''p''. Case 4.2: ''p'' begins with 4. In this case we can write ''p'' = 4''y''9, where all digits of ''y'' are 0, 3, 6, or 9. If 0 ◁ ''y'', then '''409''' ◁ ''p''. If 3 ◁ ''y'', then 43 ◁ ''p''. If 9 ◁ ''y'', then '''499''' ◁ ''p''. Hence we may assume ''y'' ∈ {6}, and thus ''p'' ∈ 4{6}9. But then ''p'' is divisible by 7, since for ''n'' ≥ 0 we have 7 × 6_''n''7 = 46_''n''9. Case 4.3: ''p'' begins with 6. In this case we can write p = 6''y''4''z''9, where all digits of ''y'', ''z'' are 0, 3, 6, or 9. If 0 ◁ ''z'', then 409 ◁ ''p''. If 3 ◁ ''z'', then 43 ◁ ''p''. If 6 ◁ ''z'', then '''6469''' ◁ ''p''. If 9 ◁ ''z'', then 499 ◁ ''p''. Hence we may assume ''z'' is empty. If 3 ◁ ''y'', then 349 ◁ ''p''. If 9 ◁ ''y'', then '''6949''' ◁ ''p''. Hence we may assume all digits of ''y'' are 0 or 6. If 06 ◁ ''y'', then '''60649''' ◁ ''p''. Hence we may assume ''y'' ∈ {6}{0}. If 666 ◁ ''y'', then '''666649''' ◁ ''p''. If 00000 ◁ ''y'', then '''60000049''' ◁ ''p''. Hence we may assume ''y'' ∈ {''𝜆'', 0, 00, 000, 0000, 6, 60, 600, 6000, 60000, 66, 660, 6600, 66000, 660000}, and thus ''p'' ∈ {649, 6049, 60049, 600049, 6000049, 6649, 66049, 660049, 6600049, 66000049, 66649, 666049, 6660049, 66600049, 666000049}, and of these numbers only '''66000049''' and '''66600049''' are primes. Case 4.4: ''p'' begins with 9. In this case we can write p = 9''y''4''z''9, where all digits of ''y'', ''z'' are 0, 3, 6, or 9. If 0 ◁ ''y'', then '''9049''' ◁ ''p''. If 3 ◁ ''y'', then 349 ◁ ''p''. If 6 ◁ ''y'', then '''9649''' ◁ ''p''. If 9 ◁ ''y'', then '''9949''' ◁ ''p''. Hence we may assume ''y'' is empty. If 0 ◁ ''z'', then 409 ◁ ''p''. If 3 ◁ ''z'', then 43 ◁ ''p''. If 9 ◁ ''z'', then 499 ◁ ''p''. Hence we may assume ''z'' ∈ {6}, and thus ''p'' ∈ 94{6}9, and the smallest prime ''p'' ∈ 94{6}9 is 946669. [[Category:Number theory]] ozdtoyp5te9l54efu5lk4am7eadc8nm 0 330631 2835353 2820405 2026-10-01T15:16:04Z Grimes2 2895877 +chords 2835353 wikitext text/x-wiki ==Basic tetrachords== The Babylonian Tonal System is based on tetrachords. 1½1, ½11, 11½ <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1 e -\tweak HorizontalBracketText.text "semitone" \startGroup f\stopGroup g} </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { e1 -\tweak HorizontalBracketText.text "semitone" \startGroup f\stopGroup g a} </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { c1 d e -\tweak HorizontalBracketText.text "semitone" \startGroup f\stopGroup} </score> and the tritone<br> 111 <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { f1 g a b} </score> Two consecutive tetrachords build a heptachord. ==Heptachord== 1½11½1 <score> \new Staff \with { \consists Ambitus_engraver \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { a1^"kitmum" b -\tweak HorizontalBracketText.text "semitone" \startGroup c\stopGroup d e-\tweak HorizontalBracketText.text "semitone"\startGroup f\stopGroup g } </score> ==7 heptachord modes== The 7 modal patterns for the Babylonian heptachords are: {| class="wikitable sortable" style="text-align: center; |+ Babylonian tonal system ! Mode !! Pattern !! Center note || Semitones || Tritones |- | ''kitmum'' || 1½11½1 || D || 10 || 0 |- | ''pītum'' || ½11½11 || E || 10 || 0 |- | ''qablītum'' || 11½11½ || C || 10 || 0 |- | ''išartum'' || 1½111½ || G || 10 || 1 |- | ''embūbum'' || ½111½1 || A || 10 || 1 |- | ''nīd qablim'' || 111½11 || B || 11 || 2 |- | ''nīš tuḫrim'' || 11½111 || F || 11 || 2 |} <score> \new Staff \with { \consists Ambitus_engraver \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { a1^"kitmum" b -\tweak HorizontalBracketText.text "semitone" \startGroup c\stopGroup d e-\tweak HorizontalBracketText.text "semitone"\startGroup f\stopGroup g } </score> <score> \new Staff \with { \consists Ambitus_engraver \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { b1^"pītum" -\tweak HorizontalBracketText.text "semitone" \startGroup c\stopGroup d e-\tweak HorizontalBracketText.text "semitone"\startGroup f\stopGroup g a} </score> <score> \new Staff \with { \consists Ambitus_engraver \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { g1^"qablītum" a b -\tweak HorizontalBracketText.text "semitone" \startGroup c\stopGroup d e-\tweak HorizontalBracketText.text "semitone"\startGroup f\stopGroup } </score> <score> \new Staff \with { \consists Ambitus_engraver \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1^"išartum" e -\tweak HorizontalBracketText.text "semitone" \startGroup f\stopGroup g a b-\tweak HorizontalBracketText.text "semitone"\startGroup c\stopGroup} </score> <score> \new Staff \with { \consists Ambitus_engraver \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c { e1^"embūbum" -\tweak HorizontalBracketText.text "semitone" \startGroup f\stopGroup g a b-\tweak HorizontalBracketText.text "semitone"\startGroup c\stopGroup d} </score> <score> \new Staff \with { \consists Ambitus_engraver \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { f,1^"nīd qablim" g a b -\tweak HorizontalBracketText.text "semitone" \startGroup c\stopGroup d e} </score> <score> \new Staff \with { \consists Ambitus_engraver \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { c1^"nīš tuḫrim" d e -\tweak HorizontalBracketText.text "semitone" \startGroup f\stopGroup g a b} </score> ==2 consecutive heptachords== <score> \new Staff \with { \consists Ambitus_engraver \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { a1^"kitmum" b -\tweak HorizontalBracketText.text "semitone" \startGroup c\stopGroup d e-\tweak HorizontalBracketText.text "semitone"\startGroup f\stopGroup g a-\tweak HorizontalBracketText.text "semitone" \startGroup bes\stopGroup c d-\tweak HorizontalBracketText.text "semitone" \startGroup es\stopGroup f} </score> Flatward shift for higher notes. ==7 consecutive heptachords== 7 consecutive heptachords build the 7 Babylonian modes: [[File:Kitmum.svg|thumb|left|1000px]] [[File:Pitum.svg|thumb|left|1000px]] [[File:Qablitum.svg|thumb|left|1000px]] [[File:Isartum.svg|thumb|left|1000px]] [[File:Embubum.svg|thumb|left|1000px]] [[File:Nid quablim.svg|thumb|left|1000px]] [[File:Nis tuhrim.svg|thumb|left|1000px]] {{clear}} ===6 cyclic consecutive heptachords=== [[File:Circle of fourths.svg|thumb|left|Circle of fourths, ''kitmum'', 36 notes, 60 semitones = Anu 𒀭]] {{clear}} ==Tuning== A tuning procedure ‘loosening’ (TU.LU) in Music of Mesopotamia for a 7-stringed instrument based on a transposition to D/D♭: <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1^"išartum" e -\tweak HorizontalBracketText.text "semitone" \startGroup f\stopGroup g a b-\tweak HorizontalBracketText.text "semitone"\startGroup c\stopGroup } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1^"kitmum" e -\tweak HorizontalBracketText.text "semitone" \startGroup f\stopGroup g a-\tweak HorizontalBracketText.text "semitone"\startGroup bes\stopGroup c } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1^"embūbum" -\tweak HorizontalBracketText.text "semitone" \startGroup es\stopGroup f g a-\tweak HorizontalBracketText.text "semitone"\startGroup bes\stopGroup c } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1^"pītum" -\tweak HorizontalBracketText.text "semitone" \startGroup es\stopGroup f g -\tweak HorizontalBracketText.text "semitone"\startGroup as\stopGroup bes c } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { des1^"nīd qablim" es f g-\tweak HorizontalBracketText.text "semitone"\startGroup as\stopGroup bes c } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { des1^"nīš tuḫrim" es f -\tweak HorizontalBracketText.text "semitone"\startGroup ges\stopGroup as bes c } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { des1^"qablītum" es f -\tweak HorizontalBracketText.text "semitone"\startGroup ges\stopGroup as bes-\tweak HorizontalBracketText.text "semitone"\startGroup ces\stopGroup } </score> ‘tightening’ (GÍD.I) <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1^"išartum" e -\tweak HorizontalBracketText.text "semitone" \startGroup f\stopGroup g a b-\tweak HorizontalBracketText.text "semitone"\startGroup c\stopGroup } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1^"qablītum" e fis -\tweak HorizontalBracketText.text "semitone"\startGroup g\stopGroup a b-\tweak HorizontalBracketText.text "semitone"\startGroup c\stopGroup } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1^"niš tuĥrim" e fis -\tweak HorizontalBracketText.text "semitone"\startGroup g\stopGroup a b cis } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { d1^"nīd qablim" e fis gis-\tweak HorizontalBracketText.text "semitone"\startGroup a\stopGroup b cis } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { dis1^"pītum" -\tweak HorizontalBracketText.text "semitone" \startGroup e\stopGroup fis gis -\tweak HorizontalBracketText.text "semitone"\startGroup a\stopGroup b cis } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { dis1^"embūbum" -\tweak HorizontalBracketText.text "semitone" \startGroup e\stopGroup fis gis ais-\tweak HorizontalBracketText.text "semitone"\startGroup b\stopGroup cis } </score> <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { dis1^"kitmum" eis -\tweak HorizontalBracketText.text "semitone" \startGroup fis\stopGroup gis ais-\tweak HorizontalBracketText.text "semitone"\startGroup b\stopGroup cis } </score> ==''kitmum'' chords== <score> \new Staff \with { \consists Horizontal_bracket_engraver \remove "Time_signature_engraver" \remove "Bar_engraver" } \relative c' { <dis fis ais>1 <eis gis b> <fis ais cis> <gis b dis> <ais cis e> <b dis fis> <cis e gis> \break <dis, fis a> <e gis b> <fis a cis> <gis b d> <a cis e> <b d fis> <cis e g> \break <d, fis a> <e g b> <fis a c> <g b d> <a c e> <b d f> <c e g> \break <d, f a> <e g bes> <f a c> <g bes d> <a c es> <bes d f> <c es g> \break <d, f as> <es g bes> <f as c> <g bes des> <as c es> <bes d f> <c es ges> \break <des, f as> <es ges bes> <f as ces> <ges bes des> } </score> ==Further reading== * {{cite conference | first = Leon | last = Crickmore | title = A New Light on the Babylonian Tonal System | conference = Proceedings of the International Conference of Near Eastern Archaeomusicology (ICONEA 2008), The British Museum, London, December 4–6, 2008, editors: Richard Dumbrill and Irving Finkel | publisher = Iconea Publications | url = https://musicircle.net/wp-content/uploads/2018/08/Crickmore-Iconea20081.pdf | place = London | year = 2008 | pages = 11-22 }} * {{cite web | title=Babylonian Tonal System | website=Allan Pettersson Fanpage | url=https://pettersson-fanpage.de/Babylon/Babylon.html | access-date=19 January 2026}} [[Category:Music theory]] [[Category:Musicology]] [[Category:Mesopotamia]] b1yu3b7npq5u2ln2m5fwf8k4tkr5yco 0 331068 2835421 2835306 2026-10-02T02:53:55Z Flickstar888 3106813 added a book chapter reference 2835421 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= doi:10.1007/s10490-021-09772-y Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] biyml9z36c0nda63bllsf2eiv7emmwj 2835423 2835421 2026-10-02T03:00:12Z Flickstar888 3106813 added a reference 2835423 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] fz75vwmuzkjl61p18wbaukjkh8vr0zh 2835424 2835423 2026-10-02T03:04:01Z Flickstar888 3106813 added a reference 2835424 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] g1nuwrzh2h6x49043l2nck0wqzrkg25 2835425 2835424 2026-10-02T03:06:23Z Flickstar888 3106813 Added a reference 2835425 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] cctspc55rqg6mu2z98g51kgmmspwn07 2835428 2835425 2026-10-02T03:10:40Z Flickstar888 3106813 Added a reference 2835428 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] fvn1em5xqsil5kukgt105tavzdup120 2835431 2835428 2026-10-02T03:15:27Z Flickstar888 3106813 Added a reference 2835431 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] 0g2ppsf7r6d8353gl8zmd3v79t1e5ea 2835448 2835431 2026-10-02T03:42:44Z Flickstar888 3106813 Added a reference 2835448 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] d5szumphyfs7omhs4zvz9ddxplfn6gp 2835451 2835448 2026-10-02T03:46:53Z Flickstar888 3106813 Added a reference 2835451 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] c6mrzu683muxxqndse1jo4i49jo0cla 2835456 2835451 2026-10-02T03:52:03Z Flickstar888 3106813 Added a reference 2835456 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] 01t5delk9vx79e0q13tv9dzgneetwvg 2835457 2835456 2026-10-02T04:06:07Z Flickstar888 3106813 Added a reference 2835457 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] m4d8hx6yar519h3g42um29dd17dcdyh 2835469 2835457 2026-10-02T08:16:21Z Flickstar888 3106813 Added YouTube videos 2835469 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] 4cakr1gqek9gemzn47t17k4dopit3xu 2835470 2835469 2026-10-02T08:19:02Z Flickstar888 3106813 Added a TedTalk reference 2835470 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] * https://www.ted.com/talks/worklife_with_adam_grant_become_friends_with_your_rivals {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] ikmt5yvqly6j0yz1au3l6cc2lnln492 2835474 2835470 2026-10-02T08:33:19Z Flickstar888 3106813 Added a ted talk on Schadenfreude 2835474 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] * https://www.ted.com/talks/worklife_with_adam_grant_become_friends_with_your_rivals * https://ideas.ted.com/do-you-secretly-feel-good-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/ {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] <references /> i8eq8cerjzkfg06dkhvbux6ew0eqxn4 2835475 2835474 2026-10-02T08:44:03Z Flickstar888 3106813 Added YouTube videos 2835475 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} {| class="wikitable" |+ '''Benign and Malicious Envy''' ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] * [https://www.youtube.com/watch?v=1f9IE3CkB4s How to Stop Comparing Yourself to Others] * https://www.ted.com/talks/worklife_with_adam_grant_become_friends_with_your_rivals * [https://ideas.ted.com/do-you-secretly-feel-good-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/ https://ideas.ted.com/do-you-secretly-feel-goo-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/] {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] <references /> oh7fshit99ya5euckq58apt32d89zik 2835476 2835475 2026-10-02T08:47:20Z Flickstar888 3106813 changed the sub heading 2835476 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ === Overview === {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} ==== '''Benign and Malicious Envy''' ==== Table 1 {| class="wikitable" ! Aspect ! Benign Envy ! Malicious Envy |- | Definition | A form of envy that motivates self‑improvement. | A form of envy that arises when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, effort, and learning. | Creates feelings of resentment, threat, or inadequacy. |- | Typical Behaviours | Working harder, learning new skills, seeking development opportunities. | Exclusion, criticism, gossip, or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into interpersonal conflict. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] * [https://www.youtube.com/watch?v=1f9IE3CkB4s How to Stop Comparing Yourself to Others] * https://www.ted.com/talks/worklife_with_adam_grant_become_friends_with_your_rivals * [https://ideas.ted.com/do-you-secretly-feel-good-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/ https://ideas.ted.com/do-you-secretly-feel-goo-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/] {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] <references /> piw27dg4rmh6w1us522digqu6qbmxa1 2835478 2835476 2026-10-02T08:52:20Z Flickstar888 3106813 /* Benign and Malicious Envy */ 2835478 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ === Overview === {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} ==== '''Benign and Malicious Envy''' ==== Table 1. {| class="wikitable" ! ! Benign Envy ! Malicious Envy |- | Definition | Envy that motivates self‑improvement. | Envy that manifests when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, motivation and learning. | Creates feelings of resentment, threat, or inferiority. |- | Typical Behaviours | Working harder, learning new skills, seeking growth or development opportunities. | Exclusion, gossip, criticism or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into workplace conflict and create a toxic culture. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] * [https://www.youtube.com/watch?v=1f9IE3CkB4s How to Stop Comparing Yourself to Others] * https://www.ted.com/talks/worklife_with_adam_grant_become_friends_with_your_rivals * [https://ideas.ted.com/do-you-secretly-feel-good-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/ https://ideas.ted.com/do-you-secretly-feel-goo-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/] {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] <references /> dueaze744z2wf3ubater3o0epgxop0y 2835481 2835478 2026-10-02T09:11:52Z Flickstar888 3106813 added previous book chapters 2835481 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ === Overview === {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian. Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} ==== '''Benign and Malicious Envy''' ==== Table 1. {| class="wikitable" ! ! Benign Envy ! Malicious Envy |- | Definition | Envy that motivates self‑improvement. | Envy that manifests when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, motivation and learning. | Creates feelings of resentment, threat, or inferiority. |- | Typical Behaviours | Working harder, learning new skills, seeking growth or development opportunities. | Exclusion, gossip, criticism or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into workplace conflict and create a toxic culture. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) * [[Motivation and emotion/Book/2010/Aggression in the workplace|Motivation and emotion/Book/2010/Aggression in the workplace - Wikiversity]] * [[Motivation and emotion/Book/2024/Rivalry in the workplace|Motivation and emotion/Book/2024/Rivalry in the workplace - Wikiversity]] {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] * [https://www.youtube.com/watch?v=1f9IE3CkB4s How to Stop Comparing Yourself to Others] * https://www.ted.com/talks/worklife_with_adam_grant_become_friends_with_your_rivals * [https://ideas.ted.com/do-you-secretly-feel-good-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/ https://ideas.ted.com/do-you-secretly-feel-goo-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/] {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] <references /> 7be0ag6vspy9k5mlql4u81asmiejond 2835483 2835481 2026-10-02T09:15:03Z Flickstar888 3106813 Added intext link to figure 1 to case study 2835483 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ === Overview === {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian (see Figure 1). Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} ==== '''Benign and Malicious Envy''' ==== Table 1. {| class="wikitable" ! ! Benign Envy ! Malicious Envy |- | Definition | Envy that motivates self‑improvement. | Envy that manifests when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, motivation and learning. | Creates feelings of resentment, threat, or inferiority. |- | Typical Behaviours | Working harder, learning new skills, seeking growth or development opportunities. | Exclusion, gossip, criticism or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into workplace conflict and create a toxic culture. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) * [[Motivation and emotion/Book/2010/Aggression in the workplace|Motivation and emotion/Book/2010/Aggression in the workplace - Wikiversity]] * [[Motivation and emotion/Book/2024/Rivalry in the workplace|Motivation and emotion/Book/2024/Rivalry in the workplace - Wikiversity]] {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] * [https://www.youtube.com/watch?v=1f9IE3CkB4s How to Stop Comparing Yourself to Others] * https://www.ted.com/talks/worklife_with_adam_grant_become_friends_with_your_rivals * [https://ideas.ted.com/do-you-secretly-feel-good-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/ https://ideas.ted.com/do-you-secretly-feel-goo-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/] {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] <references /> 8a356ofdx9lwi4nxy0nug5cx9cp88z9 2835484 2835483 2026-10-02T09:21:23Z Flickstar888 3106813 added an image 2835484 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ === Overview === {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian (see Figure 1). Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[File:Happy-smiley-face-and-sad-2048x1536.jpg|thumb|Figure 2. Envy can drive positive or negative behaviour in the workplace.]] [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} ==== '''Benign and Malicious Envy''' ==== Table 1. {| class="wikitable" ! ! Benign Envy ! Malicious Envy |- | Definition | Envy that motivates self‑improvement. | Envy that manifests when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, motivation and learning. | Creates feelings of resentment, threat, or inferiority. |- | Typical Behaviours | Working harder, learning new skills, seeking growth or development opportunities. | Exclusion, gossip, criticism or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into workplace conflict and create a toxic culture. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) * [[Motivation and emotion/Book/2010/Aggression in the workplace|Motivation and emotion/Book/2010/Aggression in the workplace - Wikiversity]] * [[Motivation and emotion/Book/2024/Rivalry in the workplace|Motivation and emotion/Book/2024/Rivalry in the workplace - Wikiversity]] {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] * [https://www.youtube.com/watch?v=1f9IE3CkB4s How to Stop Comparing Yourself to Others] * https://www.ted.com/talks/worklife_with_adam_grant_become_friends_with_your_rivals * [https://ideas.ted.com/do-you-secretly-feel-good-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/ https://ideas.ted.com/do-you-secretly-feel-goo-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/] {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] <references /> s5510u0qu71tgghixlq3sqwlo6r7qs3 2835485 2835484 2026-10-02T09:22:08Z Flickstar888 3106813 Bolded 2835485 wikitext text/x-wiki {{title|Envy in the workplace:<br>What role does envy play in workplace behaviour?}} __TOC__ === Overview === {{RoundBoxTop|theme=9}} [[File:Zonaspace-coworking-collaboration.jpg|thumb|320x320px|'''Figure 1'''. Envy can occur in any workplace.]] ;Case study Jillian and Anna work for the same consulting firm and are at the same level. Jillian recently completed a project that received recognition from senior leaders and she continues to be praised about it. Anna and Jillian get along well, although Anna has started feeling resentful towards Jillian (see Figure 1). Anna recently asked Jillian about the project and what tools she used that could possibly assist with her projects. Jillian mentioned she completed a project management course that really changed the way she approaches projects to ensure all milestones are delivered on time and on budget. Anna enrols in the same project management course immediately. This is an example of benign envy. By feeling envy towards Jillian, it has motivated Anna to take action to improve herself. With Anna developing her project management skills, this will impact the team and consulting firm in a positive way encouraging extraordinary results. {{RoundBoxBottom}} [[File:Happy-smiley-face-and-sad-2048x1536.jpg|thumb|'''Figure 2.''' Envy can drive positive or negative behaviour in the workplace.]] [[wikipedia:Envy|Envy]] is a powerful [[emotion]]. It can be described as the resentment you feel when others receive what you deeply desire. In many workplaces, it is human nature for people to compare themselves to others. In the workplace, a person will measure and compare themselves against those that are being recognised for their work, those that are promoted and those that seem more valued than they are. These comparisons can trigger envy, especially when someone feels they are inferior to others. Envy is the driver for many different workplace behaviours: * competitiveness * unfairness * catalyst for change * another example While the negative effects of envy attract the most attention, there are also positive aspects that can bring a wealth of growth and encouragement to the workplace. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is the role of envy in the workplace? * What is the difference between malicious envy and benign envy? * What causes envy and how is it linked to motivation? * What is the relationship between envy and self-efficacy? * What is the relationship between envy and social comparison theory? {{RoundBoxBottom}} == Role of envy in the workplace == There are many causes of envy in the workplace. Through guidance and intervention, envy can be used as a workplace 'tool' to drive positive behaviour. *Envy can be destructive or can lead to a promotion (Liu et al, 2021) *can drive cultural change *envy can occur when individuals compare themselves to others, they perceive to be more fortunate. == Malicious envy vs benign envy == Envy plays an important role in workplace behaviours. There are two types of workplace envy: * Benign envy * Malicious envy Malicious and benign envy both exist in workplaces. * Malicious and benign envy exist in all workplaces. * Malicious envy - negative behaviours will be described and how they influence the workplace. * Benign envy - positive behaviours will be described and how they influence the workplace. {{RoundBoxTop|theme=3}}Scenario: Jon and Sam have worked together for over a year, and both applied for a promotion within the team recently, Jon was successful and Sam missed out. Other team members have noticed lately that Sam is putting Jon down in meetings and excluding him from their team lunches. The situation appears to be escalating by the day. This is an example of malicious envy. {{RoundBoxBottom}} ==== '''Benign and Malicious Envy''' ==== Table 1. {| class="wikitable" ! ! Benign Envy ! Malicious Envy |- | Definition | Envy that motivates self‑improvement. | Envy that manifests when someone feels threatened or unable to match another’s achievements. |- | Emotional Response | Encourages growth, motivation and learning. | Creates feelings of resentment, threat, or inferiority. |- | Typical Behaviours | Working harder, learning new skills, seeking growth or development opportunities. | Exclusion, gossip, criticism or subtle sabotage. |- | Impact on Workplace Culture | Strengthens workplace culture through healthy competition and personal development. | Damages trust, teamwork, morale, and can escalate into workplace conflict and create a toxic culture. |- | Outcome | Positive: supports improvement and collaboration. | Negative: undermines relationships and workplace functioning. |} == Relationship between envy and motivation? == Envy is linked to motivation. The relationship between them is: * motivation can drive envy * what motivates positive behaviour * what motivates negative behaviour * how, what and why? == Behaviours caused by self-efficacy? == Self-efficacy is the mental switch that determines whether envy will lead to a positive or negative behaviour. The two types of self-efficacy are: * high self-efficacy * low self-efficacy * Example of each of the above == Relationship between workplace envy and social comparison theory? == Social comparison theory was introduced by Festinger in 1954. This model assumes that individuals tend to compare their opinions and/or abilities to others. Feeling threatened in the workplace makes people judge themselves more harshly as they believe they cannot match their colleague's social status or success. ==Key points== For the topic development, for each heading and sub-heading: * Provide at least three bullet-points, including for the Overview and Conclusion * Include key citations ==Figures== * Use figures to illustrate concepts, add interest, and to serve as examples * Figures can show photos, diagrams, graphs, video, audio, etc. * Embed figures throughout the chapter, starting with the scenario in the Overview section * Caption figures (use '''Figure #'''. and explain the relevance of the image to the text) * Images must be embedded from [[commons:|Wikimedia Commons]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Interactive learning features help to bring book chapters to life and can be embedded throughout the chapter. {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples describe concepts in action * Can be real or fictional; if real, provide citations * Can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Present using [[#Feature boxes|feature boxes]] {{anchor|Feature box}} ;Feature boxes * Highlight key content using [[Motivation and emotion/Wikiversity/Feature box|feature boxes]], but don't overuse, otherwise they lose their effect * Consider using feature boxes for: ** [[#Scenarios|Scenarios]], case studies, or examples ** Focus questions ** Tips ** Quiz questions ** Take-home messages ;Embedded links * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") {{anchor|Tables}} ;Tables * Use to tables to organise and summarise information * Cite each table at least once in the main text (e.g., see Table 1) * Tables should be captioned * [[Motivation and emotion/Wikiversity/Tables|More example tables]] which can be adapted '''Table 1''' A Descriptive Caption Which Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing Knowing x Self/Other {| class="wikitable" style="margin: auto; |- ! !! Known to self !! Not known to self |- | '''Known to others''' || Open area || Blind spot |- | '''Not known to others''' || Hidden area || Unknown |} ;Quizzes * Using one or two quiz questions for each main section is better than a long quiz at the end * Quiz ''conceptual'' understanding, rather than trivia. Ask about important information such as take-home messages * Ask easy rather than hard questions * Different types of quiz questions are possible; see [[Help:Quiz|Quiz]] Example simple quiz questions. Choose your answers and click "Submit": <quiz display="simple"> {Benign envy is associated with positive emotions and encourages positive behaviour? |type="()"} + True - False {Malicious envy is associated with negative emotions and encourages negative behaviour? |type="()"} - True + False </quiz> ==Conclusion== * The Conclusion will answer the questions. * The take home messages are that envy is an important catalyst for change in the workplace if driven in a positive way. * Healthy competition and influence of envy. * Role of motivation and envy in shaping workplace culture. * Draft clear take-home message(s), even at the topic development stage * Together, the [[#Overview|Overview]] and Conclusion should summarise the problem, its significance, and how psychological science contributes to understanding and addressing it. * Recommended length: 150 to 330 words {{tip|Suggestions for this section: * What is the answer to the sub-title question based on psychological theory and research? * What are the answers to the focus questions? * What are the practical, take-home messages? }} ==See also== Provide [[Help:Contents/Links#Interwiki_links|internal (wiki) links]] to the most relevant Wikiversity pages (esp. related [[Motivation and emotion/Book|motivation and emotion book chapters]]) and [[w:|Wikipedia articles]]. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * Envy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2011/Envy|title=Motivation and emotion/Book/2011/Envy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-08-25}}</ref> (Book Chapter, 2011) {{ic|See Tutorial 2 for how to create an internal link to a book chapter) * Jealousy<ref>{{Cite web|url=https://en.wikiversity.org/wiki/Motivation_and_emotion/Book/2013/Jealousy|title=Motivation and emotion/Book/2013/Jealousy - Wikiversity|website=en.wikiversity.org|language=en|access-date=2026-10-02}}</ref> is not the same as envy (Book Chapter, 2013) * [[Self-Efficacy]] (Wikipedia) * [[Motivation and emotion/Book/2010/Aggression in the workplace|Motivation and emotion/Book/2010/Aggression in the workplace - Wikiversity]] * [[Motivation and emotion/Book/2024/Rivalry in the workplace|Motivation and emotion/Book/2024/Rivalry in the workplace - Wikiversity]] {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Crusius J., Thierhoff J., Lange J. (2021). Dispositional greed predicts benign and malicious envy. Personality and Individual Differences, 168, 110361. https://doi.org/10.1016/j.paid.2020.110361 Duffy, M. K., Lee, K., & Adair, E. A. (2021). Workplace envy. Annual Review of Organizational Psychology and Organizational Behavior, 8, 19–44. https://doi.org/10.1146/annurev-orgpsych-012420-055746 Erdil O., Müceldili B. (2014). The effects of envy on job engagement and turnover intention. Procedia - Social and Behavioral Sciences, 150(1), 447–454. https://doi.org/10.1016/j.sbspro.2014.09.050 Jafri M. H. (2020). Moderating role of self-efficacy on benign envy—employee engagement relationship. Business Perspectives and Research, 8(2), 232–243. https://doi.org/10.1177/227853371988745 Köksal, K., Tufan, C., Griffiths, M.D. et al. From perceived workplace envy to deviance: a multi-theoretical model of envy-related workplace behaviors and the moderating role of social courage. Curr Psychol 45, 1052 (2026). https://doi.org/10.1007/s12144-026-09607-3 Lange, J., Paulhus, D. L., & Crusius, J. (2018). Elucidating the Dark Side of Envy: Distinctive Links of Benign and Malicious Envy With Dark Personalities. Personality and Social Psychology Bulletin, 44(4), 601-614. https://doi.org/10.1177/0146167217746340 Li M., Xu X., Kwan H. K. (2021). The antecedents and consequences of workplace envy: A meta-analytic review. Asia Pacific Journal of Management. Advance online publication. https://doi.org/10.1007/s10490-021-09772-y Li M, Qin Y, Le J (2025), "Mentoring matters: decoding the impact of downward envy on interpersonal conflict, workplace ostracism, and displaced aggression". Journal of Managerial Psychology, Vol. 40 No. 1 pp. 67–81, doi: https://doi.org/10.1108/JMP-12-2023-0768 Li, Y., & Wang, S. (2023). "Comparisons are Odious"? - Exploring the Dual Effect of Upward Social Comparison on Workplace Coping Behaviors of Temporary Agency Workers. Psychology research and behavior management, 16, 4251–4265. https://doi.org/10.2147/PRBM.S425946 Liu, H., Geng, J., & Yao, P. (2021). Relationship of Leadership and Envy: How to Resolve Workplace Envy with Leadership-A Bibliometric Review Study. Journal of Intelligence, 9(3), 44. https://doi.org/10.3390/jintelligence9030044 Nakai, A. and Numazaki, M. (2026), The Emotional Nature of Malicious and Benign Envy: Separate Measurements for Emotion and Motivation. Jpn Psychol Res. https://doi.org/10.1111/jpr.12568 Song, Y., & Zhao, Z. (2022). Social Undermining and Interpersonal Rumination among Employees: The Mediating Role of Being the Subject of Envy and the Moderating Role of Social Support. International Journal of Environmental Research and Public Health, 19(14), 8419. https://doi.org/10.3390/ijerph19148419 Su, X., & Chen, C. (2023). The Influence of Workplace Envy on Employees’ Knowledge-Hiding Behavior Based on a Comparative Analysis between Generation Cohorts. Behavioral Sciences, 13(9), 716. https://doi.org/10.3390/bs13090716 Walter CE, Au-Yong-Oliveira M (2022), "An exploratory study on the barriers to innovative behavior: the spiteful effect of envy". Journal of Organizational Change Management, Vol. 35 No. 6 pp. 936–960, https://doi.org/10.1108/JOCM-02-2022-0034 Wilkes, D. (2023) Workplace Envy: Exploring the Effect of Envy on Team Communication and Organizational Information Sharing. Open Journal of Business and Management, 11, 1757-1786. https://doi.org/10.4236/ojbm.2023.114099 Yang C and Tang R (2021) Validating the “Two Faces” of Envy: The Effect of Self-Control. Front. Psychol. 12:731451. https://doi.org/10.3389/fpsyg.2021.731451 }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://students.unimelb.edu.au/academic-skills/explore-our-resources/essay-writing/six-top-tips-for-writing-a-great-essay Six top tips for writing a great essay] (University of Melbourne) * [http://www.skillsyouneed.com/write/structure.html The importance of structure] (skillsyouneed.com) * [https://www.youtube.com/shorts/3g0lRfiAXzc Why Workplace Envy Is Secretly Power ? - YouTube] * [https://www.youtube.com/shorts/NwGMsgB9mNg Envy: The Ugliest Emotion? Find out the Truth!] * [https://www.youtube.com/watch?v=1f9IE3CkB4s How to Stop Comparing Yourself to Others] * https://www.ted.com/talks/worklife_with_adam_grant_become_friends_with_your_rivals * [https://ideas.ted.com/do-you-secretly-feel-good-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/ https://ideas.ted.com/do-you-secretly-feel-goo-when-others-stumble-5-ways-to-make-peace-with-this-very-human-emotion/] {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Envy]] [[Category:Motivation and emotion/Book/Organisational psychology]] <references /> b65dxnvme879nza59enve294s0yrtsv 0 331100 2835427 2835270 2026-10-02T03:10:22Z StretchBeyond 3105744 Corrected inconsistency in sub-heading style used (ranged from 1-4). Italicised some reference journal names as per APA7. 2835427 wikitext text/x-wiki {{title|Emotional intelligence:<br>How does emotional intelligence affect emotional wellbeing?}} __TOC__ == Overview == {{RoundBoxTop|theme=3}} [[File:Sophie emotional regulation scenario.png|thumb|'''Figure 1.''' A university student pausing to regulate her emotions after receiving a disappointing grade, generated with ai ]] '''Scenario''' Imagine Sophie, a university student managing several assessments and conflict with a close friend. After receiving a disappointing mark, she feels frustrated, embarrassed, and overwhelmed. Rather than reacting immediately, she recognises her emotions, takes time to regulate them, and later talks calmly with her friend. Another student in the same situation might become overwhelmed or react impulsively. Why might people respond differently to similar emotional situations? One explanation involves emotional intelligence, the ability to perceive, understand, use, and regulate emotions. EI may influence how people interpret and respond to emotional experiences and, consequently, their emotional wellbeing. Emotional wellbeing involves more than experiencing positive emotions or avoiding negative ones; it also concerns how people experience and manage emotions. Understanding the relationship between EI and wellbeing can help explain which emotional abilities may support wellbeing, which components are particularly important, and the psychological processes underlying this relationship. {{RoundBoxBottom}} {{RoundBoxTop}} ; Focus questions # What are emotional intelligence and emotional wellbeing? # What is the relationship between emotional intelligence and emotional wellbeing? #How does emotional intelligence influence emotional wellbeing? #Which components of emotional intelligence are particularly important for emotional wellbeing? # How can emotional intelligence be developed to support emotional wellbeing? {{RoundBoxBottom}} == What are emotional intelligence and emotional wellbeing? == Emotional intelligence can play an important role in how people recognise, understand, and regulate their emotions. These emotional abilities may influence how people cope with difficult experiences and support their overall emotional wellbeing. However, EI is a complex construct, and different emotional abilities may contribute to wellbeing in different ways. Before examining this relationship, it is important to understand what psychologists mean by emotional intelligence and emotional wellbeing. One influential approach to emotional intelligence is Mayer and Salovey's ability model, which describes emotional intelligence through four related abilities: perceiving emotions, using emotions to support thinking, understanding emotions, and managing emotions see Figure 1. An important practical question is whether emotional abilities can be developed and whether improving them leads to better wellbeing.[[File:Model of emotional intelligence.png|thumb|'''Figure 1.''' ''Mayer and Salovey's Emotional Intelligence model'' |359x359px]] === Defining emotional wellbeing === Emotional wellbeing refers to people's emotional experiences and how they evaluate their lives. Psychological research often distinguishes between hedonic and eudaimonic approaches to wellbeing. Hedonic wellbeing focuses on experiences such as pleasure, enjoyment, and comfort, whereas eudaimonic wellbeing emphasises personal growth, meaning, and authenticity (Huta & Waterman, 2014). Both approaches are important for understanding wellbeing, although researchers differ in how they define and measure these concepts. Importantly, emotional wellbeing does not mean feeling happy or positive all the time. Negative emotions such as sadness, anger, anxiety, and disappointment are normal responses to difficult experiences. Chen et al. (2023) explain that adaptive stress responses can help people cope with stressful situations or adjust to challenges that cannot be resolved, whereas maladaptive responses can increase the risk of stress-related difficulties. This highlights why wellbeing involves more than simply experiencing positive emotions; how people respond to difficult experiences is also important. Another approach to understanding wellbeing is Seligman's PERMA model, which identifies five elements of flourishing: positive emotion, engagement, relationships, meaning, and accomplishment (Al-Hendawi et al., 2024). Unlike approaches that focus mainly on emotional experiences, PERMA considers several aspects of a fulfilling life see Figure 2.[[File:ChatGPT Image Sep 26, 2026, 01 48 17 PM.png|thumb|335x335px|'''Figure 2.''' ''Seligman's PERMA model of wellbeing, consisting of positive emotion, engagement, relationships, meaning, and accomplishment. (AI generated)'' ]]<quiz display="simple"> Quiz 1. Which statement best describes emotional intelligence? |type="()"} + The ability to perceive, understand, use, and manage emotions. - The ability to avoid experiencing negative emotions. - The ability to remain happy in all situations. - The ability to control the emotions of other people. } </quiz> <quiz display="simple"> Quiz 2. What does emotion regulation involve? |type="()"} + Managing how we experience and respond to emotions. - Avoiding all negative emotions. - Staying positive in stressful situations. - Ignoring emotions until they disappear. } </quiz> === Trait emotional intelligence === Trait EI focuses on how people perceive their own emotional abilities and tendencies rather than how they perform on an objective test. It is usually measured through self-report questionnaires that assess how people typically recognise, understand, and manage emotions. In contrast, performance-based tests assess emotional abilities through emotion-related tasks. Chapman (2005) explains that trait EI is more closely related to personality, whereas ability EI is more closely associated with cognitive abilities. Performance-based measures, such as the Multifactor Emotional Intelligence Scale and Mayer-Salovey-Caruso Emotional Intelligence Test, assess responses using scoring criteria. However, determining a correct emotional response can be difficult because emotional situations may be interpreted differently. Expert scoring relies on selected experts, while consensus scoring reflects the responses of a reference group (Chapman, 2005). Trait EI avoids this scoring issue by focusing on people's perceptions of their emotional abilities. Common self-report measures include the Trait Meta-Mood Scale and the 33-item Schutte Self-Report Inventory of Emotional Intelligence (Chapman, 2005). However, people's perceptions of their emotional abilities may not always reflect their actual performance. This distinction is important when examining emotional wellbeing. Someone may believe they manage emotions effectively even when their behaviour suggests otherwise. Trait EI and wellbeing are also often measured using self-report questionnaires, which may influence the strength of the relationship observed between them (Sánchez-Álvarez et al., 2016). == What is the relationship between emotional intelligence and emotional wellbeing? == === Emotional intelligence and positive wellbeing === Research generally suggests that people with higher EI report greater subjective wellbeing. A meta-analysis of 25 studies involving more than 8,500 participants found a moderate positive association between EI and subjective wellbeing (''r'' = .32; Sánchez-Álvarez et al., 2016). This indicates that higher EI tends to be associated with greater subjective wellbeing, although the relationship is moderate rather than strong. Importantly, the strength of the relationship depended on how EI was measured. The association was stronger for self-report measures that incorporated emotional and personality-related characteristics (''r'' = .38) than for performance-based measures (''r'' = .22). EI also showed a somewhat stronger relationship with life satisfaction (''r'' = .35) than with emotional experiences (''r'' = .29). These findings demonstrate why the way EI and wellbeing are defined and measured matters when interpreting their relationship (Sánchez-Álvarez et al., 2016). However, these findings do not demonstrate that EI causes greater happiness or life satisfaction. People who already experience greater wellbeing may find it easier to perceive or manage emotions, while other characteristics, including personality, could potentially contribute to both EI and wellbeing. === Emotional intelligence and negative wellbeing === EI has also been examined in relation to psychological distress and other negative outcomes. Martins et al. (2010) found that higher EI was associated with better health outcomes, including aspects of mental health. Research has also examined relationships between emotional abilities, emotion regulation, and symptoms of depression (Fernández-Berrocal & Extremera, 2016). Importantly, higher EI does not mean that someone will never experience negative emotions. Instead, emotional abilities may influence how people understand and respond to difficult emotions when they occur. Sophie's emotional abilities, for example, do not prevent her from feeling disappointed about her grade. They may instead help her recognise the emotion and choose how to respond to it. === Trait and ability emotional intelligence === Trait EI tends to show stronger associations with wellbeing than ability EI, which is typically assessed using performance-based measures. One possible explanation is that trait EI and wellbeing are often both assessed using self-report questionnaires. Similar measurement methods can contribute to stronger observed relationships between constructs. Self-report measures also assess people's perceptions of their emotional abilities, which may not always correspond with their performance on emotional ability tasks. This makes the way EI is measured particularly important when interpreting its relationship with wellbeing === '''What does the evidence tell us?''' === Overall, research suggests that higher EI is linked to greater subjective wellbeing and lower psychological distress. However, the strength of this relationship varies depending on how EI is defined and measured (Martins et al., 2010; Sánchez-Álvarez et al., 2016). However, an association between EI and wellbeing does not demonstrate that EI directly causes better wellbeing. Much of this research is correlational, meaning the direction of the relationship cannot necessarily be established and other factors may contribute to both constructs. Differences between EI models and measurement approaches further complicate interpretation. Therefore, the evidence supports a relationship between EI and wellbeing, but stronger causal conclusions require research capable of examining whether changes in EI actually produce changes in wellbeing. Finding an association also does not explain how EI and wellbeing are connected. Emotional awareness, emotional understanding, emotion regulation, coping with stress, and social relationships may provide possible pathways through which EI is associated with emotional wellbeing. == How does emotional intelligence influence emotional wellbeing? == === Emotional awareness and perception === The relationship between emotional intelligence and wellbeing may be explained by several psychological processes. Emotional intelligence may help people recognise what they are feeling, understand why those emotions have occurred, regulate difficult emotional responses, and cope more effectively with stressful situations. It may also support communication and relationships with others. Rather than working separately, these processes are likely to interact and may help explain why people with higher emotional intelligence often report greater wellbeing. === Emotional awareness and perception === Recognising emotions is an important first step in responding to them effectively. Being able to identify whether a person is feeling anxious, angry, disappointed, or overwhelmed can provide useful information about what is happening and what they may need to do next. For example, recognising feelings of anxiety before an assessment may help a student identify the source of their stress and decide whether they need to prepare further, seek support, or use a strategy to manage their anxiety. Difficulty recognising emotions may make it harder to respond appropriately. A person who interprets anxiety as anger, for example, may react to a situation differently than someone who accurately understands what they are experiencing. Emotional awareness alone does not guarantee good emotional wellbeing, but it may provide the information needed for later processes such as emotional understanding, regulation, and coping (Lane & Smith, 2021). {{RoundBoxTop|theme=3}}💡 Tip When you experience a strong emotion, try identifying exactly what you are feeling rather than simply describing it as “good” or “bad.” For example, you might recognise that you are disappointed rather than embarrassed, or anxious rather than angry. This ability to identify emotions more precisely, known as emotional granularity, can help build emotional awareness and guide how you respond.{{RoundBoxBottom}} === Understanding emotions === Emotional intelligence also involves understanding why emotions occur and how they may change over time. Emotional experiences are not always simple, and people can experience several emotions at once. Someone receiving critical feedback, for example, might simultaneously feel disappointed, embarrassed, and motivated to improve. Understanding the causes and possible consequences of these emotions may help people choose more appropriate responses. Instead of immediately reacting to disappointment, a person who understands where the feeling comes from may be better able to consider the situation before deciding what to do (Tzieropoulos et al., 2011). Emotional understanding may therefore contribute to wellbeing indirectly by supporting more effective emotion regulation and coping. === Emotion regulation === Emotion regulation refers to how people influence their emotional experiences and responses. Rather than eliminating negative emotions, regulation can involve changing how a situation is interpreted or choosing how to respond. Different strategies may have different consequences for wellbeing. Cognitive reappraisal changes the interpretation of a situation to alter its emotional impact, however suppression reduces emotional expression without necessarily changing the underlying experience. Emotional intelligence may help people select appropriate regulation strategies, potentially explaining its relationship with wellbeing (MacCann et al., 2026). However, further evidence is needed to determine whether emotion regulation actually mediates the relationship between emotional intelligence and wellbeing. === Coping with stress === Emotional intelligence may also influence how people respond to stressful experiences. Stress can produce difficult emotional responses such as tension, worry, and feelings of being overwhelmed. Chen et al. (2023) distinguish between adaptive responses that help people cope with or adjust to stressors and maladaptive responses that may interfere with functioning and increase the risk of stress-related difficulties. Emotional skills may be useful during this process because recognising and understanding an emotional response can help a person decide how to cope with the situation. Effective coping does not necessarily remove the stressor, particularly when a situation cannot be changed. Instead, people may need to adjust their response to it. Emotion regulation has also been identified as a resilience-related factor, further demonstrating the connection between emotional processes and responses to stress. === Social relationships and support === Emotional intelligence may also contribute to wellbeing through relationships with other people. Recognising another person's emotions can make it easier to understand their perspective, communicate appropriately, and respond to interpersonal difficulties. Managing one's own emotional responses may also be important during disagreements or emotionally challenging conversations. These abilities could support stronger relationships and access to social support, providing another possible pathway between emotional intelligence and wellbeing. However, being able to recognise another person's emotions does not automatically lead to supportive or prosocial behaviour (Hidalgo-Fuentes et al., 2024). Emotional abilities describe how effectively emotional information is processed, rather than whether that information will always be used positively. '''Figure 3.''' ''Possible pathways through which emotional intelligence may support emotional wellbeing.'' Emotional intelligence may contribute to emotional wellbeing through several interacting processes, including emotional awareness, emotional understanding, emotion regulation, coping with stress, and social functioning. These processes may influence one another rather than occurring in a simple step-by-step sequence. == Which components of emotional intelligence are particularly important for emotional wellbeing? == Although emotional intelligence is often discussed as a single construct, Mayer and Salovey's ability model proposes several distinct emotional abilities. These components may not contribute equally to emotional wellbeing. Comparing emotion perception, using emotions, emotional understanding, and emotion management can therefore provide a clearer picture of which aspects of emotional intelligence may be particularly relevant to wellbeing. === Emotion perception === Emotion perception involves accurately recognising emotions in oneself and other people. This ability may contribute to wellbeing by helping individuals identify their emotional state and recognise emotional information in social situations. However, recognising an emotion does not necessarily mean that a person knows how to respond to it. Someone may accurately recognise that they are angry, for example, while still responding impulsively. Emotion perception may therefore provide an important foundation for emotional functioning without being sufficient on its own to support wellbeing (Carfagno, 2020). === '''Using emotions''' === Using emotions involves drawing on emotional information to support thinking, attention, judgement, and decision-making. Different emotional states can influence what people notice and how they approach a problem. Being able to use this information may therefore help individuals adapt their thinking to different situations. However, the relevance of this component to emotional wellbeing needs to be established through research rather than assumed (Blasco-Belled et al., 2019). Compared with emotion management, for example, using emotions may have a less direct connection with how people cope with distress or regulate difficult emotional experiences. === Emotion understanding === Emotion understanding involves recognising the causes of emotions, distinguishing between related emotional states, and understanding how emotions can change or combine. This ability may help people make sense of complicated emotional experiences and anticipate how feelings might develop. Understanding an emotion may also make it easier to choose an appropriate coping or regulation strategy. However, as with emotion perception, understanding an emotion does not guarantee that it will be managed effectively. Research comparing the different branches of emotional intelligence is therefore needed to determine whether emotional understanding has an independent relationship with wellbeing or primarily contributes through other emotional processes (Antonopoulou, 2024). === Emotion regulation and management === Emotion management may have a particularly direct connection with emotional wellbeing because it concerns how people respond to and regulate emotional experiences. Effective regulation could help people manage distress, maintain positive emotional functioning, and recover from stressful experiences. This does not mean eliminating negative emotions, but responding to them in ways that are appropriate to the situation. However, emotion management should not automatically be considered the most important component of emotional intelligence. Its relative importance needs to be established by studies that compare it directly with perception, use, and understanding of emotions. Differences in how emotional intelligence and wellbeing are measured may also affect which component appears most strongly related to wellbeing (Blasco-Belled et al., 2019). === Comparing the components === Overall, the four emotional abilities may contribute to wellbeing in different but connected ways. Perception provides information about emotional states, understanding helps make sense of that information, using emotions may support thinking and decision-making, and management concerns how emotional experiences are handled. Rather than functioning independently, these abilities may work together. Determining whether one component is particularly important requires direct comparisons across the four branches. Evidence that emotion management is associated with wellbeing would not, by itself, demonstrate that it is more important than the other components. Differences between ability-based and self-report measures should also be considered when interpreting these findings. <quiz display="simple"> Quiz 3. Which statement best describes how the components of emotional intelligence relate to wellbeing? |type="()"} + Different EI components may contribute to wellbeing in different but connected ways. - Emotion management is always the most important component for wellbeing. - Emotion perception alone is enough to support emotional wellbeing. - All EI components affect wellbeing in exactly the same way. } </quiz> <quiz display="simple"> Quiz 4. Why might recognising an emotion not be enough to support wellbeing? |type="()"} + A person may recognise an emotion but still respond to it poorly. - Recognising emotions prevents people from regulating them. - Emotion perception only involves recognising other people's emotions. - Recognising emotions automatically removes negative feelings. } </quiz> '''Table 2.''' ''Emotional intelligence components and wellbeing'' {| class="wikitable" !EI component !What it involves !Relevance to wellbeing |- |'''Emotion perception''' |Recognising emotions |Supports emotional awareness |- |'''Using emotions''' |Using emotions to guide thinking |Supports attention and judgement |- |'''Emotion understanding''' |Understanding causes and changes in emotions |Supports understanding and responding |- |'''Emotion management''' |Regulating emotional responses |Supports coping and emotional functioning |} == How can emotional intelligence be developed to support emotional wellbeing? == If emotional intelligence contributes to wellbeing, an important practical question is whether these emotional abilities can be developed. Emotional intelligence interventions have attempted to improve skills such as emotional awareness, understanding emotions, emotion regulation, and interpersonal communication. However, evidence that EI can be improved does not necessarily mean that increasing EI will automatically improve emotional wellbeing. === Can emotional intelligence be developed? === Emotional intelligence is not necessarily a completely fixed characteristic. Training programs have attempted to develop emotional abilities through education, practice, feedback, and exercises focused on recognising and managing emotions. However, the effectiveness of training may depend on how emotional intelligence is conceptualised and measured. Changes in self-reported EI, for example, may indicate that people feel more confident in their emotional abilities without necessarily demonstrating equivalent improvements on performance-based measures. Research evaluating EI interventions is therefore important for determining whether emotional abilities can genuinely be improved and whether any improvements continue after training has ended (Hodzic et al., 2017). === Emotional intelligence interventions === EI interventions may target several skills rather than emotional intelligence as a single ability. Activities can focus on recognising emotional cues, developing emotional vocabulary, understanding emotional triggers, considering other people's perspectives, practising emotion-regulation strategies, and improving emotional communication. These approaches are particularly relevant to emotional wellbeing if improvements in emotional skills help people respond more effectively to stress and difficult emotional experiences. However, intervention studies need to examine more than whether EI scores increase. They should also assess whether changes are accompanied by meaningful improvements in wellbeing. === Do improvements in emotional intelligence improve wellbeing? === An important distinction is whether EI training improves emotional intelligence itself and whether those improvements subsequently lead to better wellbeing. An intervention could increase participants' knowledge about emotions without meaningfully changing their happiness, life satisfaction, stress, or emotional functioning. Evidence that an intervention improves both EI and wellbeing would provide stronger support for a possible causal relationship than correlational studies showing that the two are associated. Even then, researchers need to consider whether improvements are maintained over time and whether changes in wellbeing are actually explained by increased emotional intelligence (Hodzic et al., 2018; Nadler et al., 2020). === Limitations and practical implications === Although EI training may have practical value, its potential benefits should not be overstated. Emotional wellbeing is influenced by many personal, social, and environmental factors, and improving emotional skills cannot remove every source of stress or psychological difficulty. Differences between EI models, measurement methods, intervention designs, and participant groups can also make findings difficult to compare. ==Conclusion== Emotional wellbeing involves more than simply feeling happy or avoiding negative emotions. It also involves how people understand, respond to, and manage their emotional experiences. Overall, emotional intelligence may support emotional wellbeing by helping people recognise, understand, and regulate emotions and respond more effectively to stressful and interpersonal experiences. Research generally shows that higher EI is associated with better indicators of wellbeing, although the strength of this relationship varies depending on how EI and wellbeing are defined and measured. Importantly, emotional intelligence should not be viewed as a guarantee or universal cause of emotional wellbeing. Wellbeing is influenced by many factors, and emotionally intelligent people will still experience stress, disappointment, conflict, and other difficult emotions. Sophie's situation demonstrates this distinction. Her emotional abilities do not prevent her from feeling disappointed or overwhelmed; instead, they may help her recognise what she is experiencing, understand why she feels that way, regulate her response, and choose behaviours that better support her wellbeing ==See also Internal Links == * [[Motivation and emotion/Textbook/Emotion/Emotion management|Managing emotions]] * [https://en.wikipedia.org/wiki/Subjective_well-being?wprov=srpw1_1 Subjective wellbeing] (Book chapter, 2026) * [[Motivation and emotion/Book/2011/Emotional intelligence|Emotional intelligence]] (Book chapter, 2011) * [[wikibooks:Foundations_of_Education_and_Instructional_Assessment/Effective_Teaching/Intelligence#Introduction_to_Emotional_Intelligence|How are all children smart?]] (Wikibooks) ==References== {{Hanging indent|1= Antonopoulou, H. (2024, April 11). The value of emotional intelligence: Self-awareness, self-regulation, motivation, and empathy as key. ''Technium Education and Humanities'' . ResearchGate. https://www.researchgate.net/publication/379764627_The_Value_of_Emotional_Intelligence_Self-Awareness_Self-Regulation_Motivation_and_Empathy_as_Key_Components Al-Hendawi, M., Alodat, A., Al-Zoubi, S., & Bulut, S. (2024). A PERMA model approach to well-being: A psychometric properties study. ''BMC Psychology'', 12(1). https://doi.org/10.1186/s40359-024-01909-0 Blasco-Belled, A., Rogoza, R., Torrelles-Nadal, C., & Alsinet, C. (2019). Emotional intelligence structure and its relationship with life satisfaction and happiness: New findings from the bifactor model. ''Journal of Happiness Studies'', 21(6), 2031–2049. https://doi.org/10.1007/s10902-019-00167-x Chapman, B. P. (2005). Emotional intelligence at mid life: A cross sectional investigation of structural variance, social correlates, and relationship to established personality and ability taxonomies. Proquest.Com. https://www.proquest.com/psychology/docview/305400900/8D98674B36744231PQ/2?accountid=28889&sourcetype=Dissertations%20&%20Theses Chen, C., Kotozaki , Y., Okubo , R., & Nakagawa , S. (2023, July 13). Editorial: New insights into stress coping and resilience . Canberra.Edu.Au. https://pmc-ncbi-nlm-nih-gov.ezproxy.canberra.edu.au/articles/PMC10374303/ Hidalgo-Fuentes, S., Martínez-Álvarez, I., Sospedra-Baeza, M. J., Martí-Vilar, M., Merino-Soto, C., & Toledano-Toledano, F. (2024). Emotional intelligence and perceived social support: Its relationship with subjective well-being. ''Healthcare'' (Basel, Switzerland), 12(6), 634. https://doi.org/10.3390/healthcare12060634 Hodzic, S., Scharfen, J., Ripoll, P., Holling, H., & Zenasni, F. (2017). How efficient are emotional intelligence trainings: A meta-analysis. ''Emotion Review'', 10(2), 138–148. https://doi.org/10.1177/1754073917708613 Huta, V., & Waterman, A. S. (2014). Eudaimonia and its distinction from hedonia: Developing a classification and terminology for understanding conceptual and operational definitions. ''Journal of Happiness Studies'', 15(6), 1425–1456. https://doi.org/10.1007/s10902-013-9485-0 Lane, R. D., & Smith, R. (2021). Levels of emotional awareness: Theory and measurement of a socio-emotional skill. ''Journal of Intelligence'', 9(3), 42. https://doi.org/10.3390/jintelligence9030042 Martins, A., Ramalho, N., & Morin, E. (2010). A comprehensive meta-analysis of the relationship between emotional intelligence and health. ''Personality and Individual Differences'', 49(6), 554–564. https://doi.org/10.1016/j.paid.2010.05.029 MacCann , C., Double , K. S., & E Clarke , I. (2026). Lower avoidant coping mediates the relationship of emotional intelligence with well-being and ill-being. Canberra.Edu.Au. https://pmc-ncbi-nlm-nih-gov.ezproxy.canberra.edu.au/articles/PMC9396212/ Nadler, R., Carswell , J., & Minda, J. P. (2020, February). Online mindfulness training increases well-being, trait emotional intelligence, and workplace competency ratings: A randomized waitlist-controlled trial. Canberra.Edu.Au. https://pmc-ncbi-nlm-nih-gov.ezproxy.canberra.edu.au/articles/PMC7048000/ Sánchez-Álvarez, N., Extremera, N., & Fernández-Berrocal, P. (2015). The relation between emotional intelligence and subjective well-being: A meta-analytic investigation. ''The Journal of Positive Psychology'', 11(3), 276–285. https://doi.org/10.1080/17439760.2015.1058968 Tzieropoulos, H., Peralta, R. G. de, Bossaerts, P., & Andino, S. L. G. (2011). The impact of disappointment in decision making: Inter-individual differences and electrical neuroimaging. ''Frontiers in Human Neuroscience'', 4(235). https://doi.org/10.3389/fnhum.2010.00235 }} ==External links== * [https://www.ted.com/talks/maximilian_park_emotional_intelligence_from_a_teenage_perspective Emotional Intelligence From a Teenage Perspective] * [https://rickhanson.com/being-well-podcast-emotional-intelligence-improving-self-awareness-self-regulation-and-empathy-2/ Being Well Podcast: Emotional Intelligence: Improving Self-Awareness, Self-Regulation, and Empathy] * [https://www.youtube.com/watch?v=4KbSRXP0wik Emotion, Stress, and Health: Crash Course Psychology #26] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Emotional intelligence]] [[Category:Motivation and emotion/Book/Well-being]] lkpmlrjf9akm9ygromznns9on616zsk 0 331144 2835459 2834794 2026-10-02T04:43:40Z U3246286 3105520 minor changes 2835459 wikitext text/x-wiki {{title|Self-determination theory and military veteran reintegration:<br>How do autonomy, competence, and relatedness shape psychological adjustment after military service?}} __TOC__ ==Overview== {{RoundBoxTop|theme=5}} ;Scenario [[File:Military-to-civilian reintegration.png|thumb|'''Figure 1'''. Transition from military service to civilian life]] What happens when the thing that gave your life structure suddenly vanishes? For many military veterans, leaving the service gains them freedom, but freedom can also bring uncertainty. After 15 years of military service including posting and deployments, a veteran returns home expecting civilian life to feel like freedom (see Figure 1) . Instead, freedom feels disorientating. For over a decade, their days were shaped by established routines, explicit expectations, clear responsibilities, a sense of belonging and being part of a team. Roles were understood. Decisions had purposes. Belonging was built into day-to-day life. The team was your support. Then, almost, overnight, the rules had changed. There are no longer orders telling them what needs to be done, no team waiting or relying on them, and no familiar structure defining what it means to be successful. Decisions that were once straightforward, now require navigating through uncertainty and often with little guidance or support. The confidence they had developed through military service may not cleanly translate into civilian life, whilst the relationships that brought connection and belonging may suddenly be hundreds or thousands of kilometres away. Disconnection is real. What was supposed to be liberation has now become a profound psychological adjustment. Self-determination theory provides an understanding of why. If military life has shaped how a veteran experiences autonomy, relatedness and competence {{ic|APA style uses serial commas}} , what happens when the life that once supported or constrained these needs is removed? {{RoundBoxBottom}}Military-to-civilian [wikilink military and civilian] transition is a major period of adjustment that brings an increased likelihood of psychosocial risk. This transition involves simultaneous changes to daily structure, social relationships, occupational roles, their identity and sources of purpose. These changes can challenge veteran's wellbeing, motivation, and psychological adjustment as they adapt to a new environment. These transitions can have long-term implications to their wellbeing with 78% of Australian defence members experienced a difficult transition and 50% were still struggling after 10 years (Romanik, et al. 2024). Self-determination theory (SDT) provides a framework for understanding psychological adjustment by suggesting that autonomy, competence, and relatedness are basic psychological needs that are fundamental for wellbeing, quality of life and psychological flourishing. Autonomy involves experiencing a sense of volition and choice, competence refers to feeling satisfactory and capable in their skills and relatedness, and relatedness by feeling connected to and valued by others (Ryan & Deci, 2022). Satisfaction of these needs support more autonomous motivation and positive psychological outcomes, whereas, frustration can undermine both wellbeing and motivation. This chapter applies SDT to military-to-civilian reintegration, it explores how military experiences and their transition to civilian life can either support or frustrate veterans' autonomy, competence, and relatedness. It'll examine how changes in these psychological needs may shape or influence veterans' emotional wellbeing, psychological adjustment and motivation. Finally this chapter will consider how SDT-informed interventions can both support need satisfaction and facilitate a successful reintegration. * '''SDT as the theoretical framework [introducing main theory that will be discussed throughout chapter]''': * SDT is a useful framework and provides a key blueprint for understanding the motivational basis of personality and social behaviour, along with the relation of basic psychological needs for wellbeing, psychological flourishing and positive quality of life (Deci, Ryan 2022). * SDT proposes that autonomy, competence, and relatedness are basic psychological needs that contribute to individuals' wellbeing and adaptive functioning. Satisfaction of these needs will contribute to positive wellbeing, whereas, frustration can contribute to negative psychological outcomes (Ryan, et al. 2022). * This chapter will therefore utilise SDT to examine how changes associated with military to civilian reintegration may influence these three psychological needs. * '''Reintegration and psychological adjustment [what do these three needs affect]:''' Following discharge (or voluntary leaving) veterans may need to reconstruct these psychological needs within unfamiliar civilian environments. * Employment difficulties may then challenge competence, whilst their loss of military relationships and identity may undermine their belonging and relatedness. Greater freedom may support their autonomy, but can also create uncertainty without their consistent military structure (Carra, et al. 2022). * This book chapter will therefore examine how these changes may shape veterans' psychological adjustment during reintegration and consider how understanding veterans' psychological needs can inform approaches/implementations to supporting successful transitions. Author note: depending on how book chapter flows along with word count, the following 'sections' may be included in the overview and structured accordingly. * '''Military service and psychological needs (Carra et al. 2022):''' transitions can have a significant adverse effect on veterans' wellbeing. The transitions usually involve simultaneous changes across multiple aspects of their life, this includes, their identity, finances, occupation, residences, routines, relationships and social support. These changes may accumulate to an increase in vulnerability to psychological distress and mental health difficulties. Research has highlighted the importance of providing suitable transition support to effectively assist veterans in navigating these changes and adapting comfortably in civilian life. {{RoundBoxTop|theme=5}} ;Focus questions {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} 1. How does Self Determination Theory {{ic|Use APA style for capitalisation of theories (lower case)}} explain psychological adjustment during military-to-civilian transition? 2. How does satisfaction or frustration of autonomy, competence, and relatedness shape veterans' motivation and emotional wellbeing? 3. How military experiences and reintegration shape autonomy, competence, and relatedness? 4. How can Self Determination Theory informed interventions support psychological need satisfaction and successful reintegration? {{RoundBoxBottom}} == How does Self Determination Theory explain psychological adjustment during military-to-civilian transition? == {{ic|The first two bullet points could make for an effective Overview}} Self-determination theory is an organismic and dialectical framework of human motivation and personality that was developed by Edward Deci and Richard Ryan. SDT offers an understanding for how motivation and psychological wellbeing are shaped by the interaction between individuals and their environments. Instead of viewing motivation as solely an individual characteristic, SDT suggests that social context can create conditions that either support healthy psychological development or contribute to difficulties in psychological functioning. A key principle of SDT is that people require satisfaction of three basic psychological needs, autonomy, competence, and relatedness to function effectively. === What is Self Determination Theory (SDT)? === SDT proposes that people have an inherent tendency towards development and growth, but social environments could either support or interfere with this process. *Autonomy is the core psychological need to feel like the author of your own life, those that are autonomous want their actions to match their true values and choices rather than being forced or controlled by external pressures. Competence refers to feeling effective and satisfactory in their capacity, is not an attained skill or capability but is instead a felt sense of confidence. Relatedness refers to feeling connected to others and caring for and by others, along with having a sense of belongingness in both with other individuals and with their community (Ryan et al. 2022). *Need satisfaction vs. need frustration. Need satisfaction drives psychological growth and well-being whilst need frustration (active blocking of these needs), can cause distress, maladaptive behaviours and ill-being (Olafsen, et al. 2021). See Table 1 below for a more in-depth explanation of these needs. {| class="wikitable" |+Table 1. Need Satisfaction vs Need Frustration (Olafasen, et al. 2021) ! !Autonomy !Competence !Relatedness |- |Need satisfaction |experiencing choice, self-direction, freedom in ones' actions |experiencing mastery, capability and effectiveness in skills. |feeling a warm, secure and mutual care with others. |- |Need frustration |feeling controlled, pressured or compelled to act in an unwanted way |feeling incompetent, facing frequent failure and doubting abilities. |experiencing loneliness, alienation, and social exclusion. |} * SDT also focuses on different forms of motivation which range from autonomous to controlled motivation and how the outcome relates to vitality, engagement, performance and psychological health (Loverre, et al. 2024). Autonomous motivation includes intrinsic motivation and fully internalised extrinsic motivation whilst controlled motivation involves external demands or internal pressures (Rybakovaite, et al. 2021). * SDT offers a unique explanatory value by connecting environmental changes to motivation, wellbeing, and psychological need satisfaction. Many theories try to explain identity, resource loss or group motivation as a primary motivator, SDT helps explain why changes influence veterans' psychological adjustment. === The Military Environment === The military environment is often characterised by routines, clearly defined roles, hierarchy, rules, expectations, collective goals and a sense of purpose, thus, creating a highly structured social environment. The military environment may support competence, autonomy and belonging through structured roles, occupation, training responsibilities, teamwork, unit cohesion and shared military identity. However, it's important to note that the hierarchy, externally imposed responsibilities and rules may create tensions with autonomy and might influence the extent to which motivation is either autonomous or controlled. *Veterans may experience feelings of cultural dislocation, emotional distress and identity disorientation which can be linked to the loss of structured military roles and routines. They may also experience social alienation when attempting to rebuild relationships, re-establish belongings, and adapt to unfamiliar social norms beyond the military sphere. The current known challenges that ADF members experience are cumulative effects of trauma and stress, moral injury to beliefs and expectations, stigma, and impaired help seeking (Kerr, et al 2022) along with the loss of relationships. * For those that may have left involuntarily often tend to experience difficulties in translating military skills into employment, and have a perceived lack of competence (Kerr, et al 2022). These challenges and difficulties may influence veterans' motivation and psychological wellbeing. * Therefore, military experiences may simultaneously constrain and support psychological needs rather than being universally positive or negative. == How does satisfaction or frustration of autonomy, competence and relatedness shape veterans' motivation and emotional wellbeing? == * Psychology need satisfaction provides a mechanism with social environments may either positively or negatively alter their wellbeing, motivation, and psychological adjustment during their transition. * SDT conceptualises motivation along a continuum of self-determination, it ranges from intrinsic motivation and forms of autonomous extrinsic motivation to then controlled forms of extrinsic motivation and amotivation. === Autonomy and the experience of choice === * SDT identifies autonomy as a psychological need that concerns psychological self-direction, freedom, and experiencing one's actions as congruent and self-endorsed with their values and interests. * Autonomy refers to the feeling of psychological freedom and self-directions of one's thoughts, actions and feelings. * Military hierarchy does not inherently undermine or satisfy autonomy. Anatomy can be experienced within structured environments, by endorsing externally induced requests by clearly understanding the meaning and purpose behind the demanded activity. Autonomy satisfaction is critical human growth and has been linked to strong levels of individual wellbeing, life satisfaction and vitality (Grimell, 2024). * Autonomy frustration can occur when military personnel sense of volition is actively undermined, this could be due to micromanagement or heavy restrictions which can correlate to internal conflicts and/or a passive/resistant mindset. This contributes to a negative psychological outcomes with links to controlled motivation, mental health issues and higher discharge rates. Further, autonomy frustration can lead to reduced trust, unit cohesion and initiative (Grimell, 2024). * Whilst transition from military to civilian life, veterans may move from an environment strongly characterised by externally prescribed relationships and structured expectations/routines, therefore, they will have a greater responsibility when it comes to employment, relationships and future goals. * Notably, greater choice does not equate to greater autonomy as whilst choices may create opportunities, choice alone does not guarantee autonomy. Especially, if veterans feel pressure, lack meaningful alternatives and have a level of uncertainty when it comes to navigating civilian life. === Competence and the sense of capability === * Competence satisfaction refers to experiencing 'mastery', growth and effectiveness in skills. In the military this could translate to feeling effective and capable of mastering tactical, physical and technical demands. Frustration involves feeling ineffective, unable to succeed and incapable (Tillberg, et al. 2026). *Military training and their clearly defined roles may provide opportunities for feedback and achievement, which would help support competence. *However, transition may challenge these experiences when veterans encounter unfamiliar workplaces and/or struggle to communicate and translate their skills effectively. Study highlighted that a significant challenge for veterans' perceived competence was translating their military skills into civilian employment. However, successful job-search experiences, or discharging straight into a job may help restore/improve competence. Therefore, successful employment may have psychological influence beyond just financial security and could provide purpose, competence and structure (Tillberg, et al. 2026). === Relatedness and the need to belong === * Relatedness satisfaction involves mutual care, belonging and connections, whilst frustration can bring rejection, loneliness, alienation or exclusion. * Military service is known for providing strong sources of relatedness through unit cohesion, teamwork, shared military identity and experiences. Leaving the military has been found to disrupt established social networks and require veterans to develop new sources of connection within civilian communities (Barnett, et al. 2021). * Maintaining military connections may support some veterans in the transition, however, developing civilian social identities may be important for long-term adjustment. === Motivation and wellbeing === * The satisfaction of autonomy, competence and relatedness are essential for optimal functioning and wellbeing. The satisfaction of these needs provide positive organisational outcomes with a more positive attitude and less turnover intentions, stronger psychological understanding, and more positive health and overall well-being. Satisfaction of these needs also create a higher likelihood of intrinsic motivation (Linden, et al. 2026). * Autonomous motivation includes intrinsic motivation and positive internalised forms of extrinsic motivation, controlled motivation comprises of internal contingencies or external pressure. This distinction may be significant to veterans establishing new employment, social, educational and personal goals following discharge (Linden, et al. 2026). * ''Author note: maybe incorporate the 'why' behind their behaviour and how that is either positive or detrimental to motivation'' === Interacting needs === * Importantly, these three needs should not be considered completely independent as SDT conceptualises them as interrelated that collective contribute to optimal function and positive psychological wellbeing (Mobbs, et al. 2018). * Frustration in one area may also coincide with difficulties/challenges in another. * ''Author note: focus on research/studies examining the combinations and interactions between satisfaction/frustration rather than just an isolated predictor.'' == How does military experiences and reintegration shape autonomy, competence and relatedness? == * The psychological impact of military service can be shaped by the environment in which personnel operate, including the way that structure, occupational roles, leadership and social relationships are experienced (Barnett, et al. 2022). * The military service shouldn't be viewed as uniformly supportive or restrictive, it's important to factor which environmental conditions frustrate or facilitate psychological needs. * Reintegration changes these conditions irrespective of whether they were positive or negative environments, thus, requiring veterans to navigate new experiences, expectations, relationships and roles whilst renegotiating sources of autonomy, belonging and competence, see figure 2.[[File:Military to civilian transition.png|thumb|Figure 2: Environmental changes experienced during military-to-civilian reintegration]] * SDT therefore can be used to examine the conditions to which military experiences either support or undermine psychological need satisfaction, rather than assuming that military service is inherently beneficial or harmful. === Structure, hierarchy, and autonomy === * Military organisations rely heavily on rules, hierarchy, orders and clear responsibilities, shaping a high level of structure that is not often seen in civilian environments. * Structure is not inherently autonomy-thwarting as dependent as, structure can provide guidance, predictability, autonomy and clear expectations, especially, when personnel understand and endorse the purpose behind their responsibilities (Barnett, et al. 2021). * Leadership plays an integral role in satisfying autonomy (Knevelsrud, et al. 2023). In particular, autonomy-supportive leadership style is where leaders empower employees to make choices, share rationales, take perspectives and minimise unnecessary pressure. An autonomy-supportive leadership brings benefits of an higher engagement, positive wellbeing and enhanced performance (Knevelsrud, et al. 2023). * However, highly controlling environments may impede autonomy when their behaviour is experienced as pressured or coerced. This might be done through actions of micromanagement and excessive pressure, these may contribute to controlled motivation and poor psychological outcomes (Barnett, et al. 2021). * This creates an important distinction between control and structure, and that leadership style and individual interpretation. * Following either voluntary or involuntary discharge, veterans may experience substantially greater choice over relationships, future goals and employment, however, greater freedom does not necessarily equate to greater autonomy when personnel experience pressure, uncertainty or lack of meaningful alternatives. <quiz display=simple> {'''When can military structure support autonomy?''' |type="()"} + When personnel understand and value their purpose - When all choices are removed - When personnel experience coercion and external pressure - When responsibilities are increased {'''Which psychological need may be most affected when a veteran loses their military unit after discharge?''' |type="()"} - Competence + Relatedness - Belonging - Autonomy </quiz> === Training, occupational roles, and competence === * Military training can provide repeated opportunities and clearly defined occupation roles that enable feedback, skill development and achievement which supports competence. * Veterans may leave the service with diverse interpersonal and technical skills with a primary focus on leadership, management, communication, adaptability and teamwork. However, even though these skills can be transferable skills, it doesn't necessarily mean that veterans will experience or have their competence recognised within civilian employment and environments (Tillberg, et al. 2026). * A recurring challenge that veterans experience, is translating military-specific experience into skills that civilians will understand, this makes it challenging for veterans to confidently communicate the relevance of the capabilities. Difficulty translating skills can contribute to unsuitable employment, unemployment, despite veterans possessing valuable capabilities (Tillberg, et al. 2026). * This further highlights the important distinction between actual competence and perceived competence. Veterans may be highly capable whilst simultaneously experiencing uncertainty about their effectiveness in civilian environments. * Research from Becker, et al. 2022 involved 31 Aus Defence Force Members who had transitioned into civilian employment had identified challenges with career integration and adaptation, which further highlights the significance of organisational practices in helping veterans navigate employment and supporting longer-term retention. * From an SDT perspective, civilian employment may restore or strengthen competence through meaningful work and recognition, but could frustrate competence when their skills are overlooked or poorly aligned to available roles. * Successful vocational reintegration involves more that just securing employment, it about creating opportunities for veterans to recognise, demonstrate and develop their capabilities within their new occupational environment. === Relatedness: from military cohesion to civilian belonging === * Military service provides strong opportunities for relatedness through teamwork, unit cohesion, camaraderie, shared identity and goals. Consequently, belonging can become deeply embedded within the military environment which makes the loss of these social connections during the transition incredibly significant for their psychological adjustment (Barnett, et al. 2021). * SDT has demonstrated that shared experience and collective goals can shape a strong sense of social support and belonging. * Discharge can disrupt these established networks, which requires veterans to reconstruct social connection within civilian communities. * The relationship between belonging and military identity is incredibly complex, research from Flake and Kite 2021, used data from 358 Australian Defence Members and identified that identity change during the transition process can involve themes of loss, poor wellbeing, social isolation along with psychosocial transition challenges. This is in conjunction with sometimes an unwillingness to relinquish a dominant military identity can contribute to social disconnectedness which is seen through withdrawal or antisocial behaviour and while reinforcing a divide between military and civilian life. Subsequently, a disconnectedness from both the military and civilian environments increases the likelihood of a decreased effort to re-connect psychosocially which would support personal growth. Although, some aspects of military identity were associated with stronger connectedness and belonging (Barnett, et al. 2021). * A positive, protective trait that was found in research is that veterans with personal agency, pushing beyond existing boundaries and a willingness to evolve were identified as themes/traits that are associated with an effective transition (Barnett, et al. 2021). * This continues to reinforce the idea that successful reintegration may involve a veteran's source of belonging rather that just replacing their military community with a civilian one. * ''Key Point: the challenge is not just simply losing relationships, but losing an environment that embedded belonging into everyday life.'' === Identity and purpose === * The military structure is not inherently need-thwarting or need-supportive, the psychological impact depends on how rules, expectations and authority are experienced and communicated. * Structure can provide clear expectations and guidance, whereas, controlling practices may pressure individuals to behave in certain ways which consequently may undermine their sense of autonomy. * Military service is an important source of status, identity, purpose and social connection, especially, when an individual's role is clearly defined. * Leaving the military may involve loss of more than just employment and may experience uncertainty about their identity when their previous role is no longer a part of their everyday life. Research has revealed that loss of military identity, status and purpose as recurring aspects and challenges during the transition. * Veterans can go through identity renegotiation as they determine what aspects of military identity are meaningful and whether they would be useful in civilian settings. * Therefore, this complexity is important when considering the transition that military personnel experience as they leave an environment that was simultaneously structured and psychologically supportive but also restrictive in other ways. * ''Key highlight is whether military structure supports internalisation and psychological need satisfaction or becomes experienced as need thwarting and controlling.'' <br /> == How can Self Determination Theory informed interventions support psychological need satisfaction and successful integration? == * Understanding how psychological challenges of military-to-civilian transition provides a key basis for considering how transition support can promote rather than undermine psychological need satisfaction. * An SDT-informed approach reorients the focus from simply helping veterans cope with change to instead, creating social environments that support autonomy, competence and relatedness. * Therefore, existing transition support should be considered in terms of whether it provides opportunities for mastery, choice and meaningful social connection. === Creating supportive transition environments === * Reintegration support should address psychological as well as practical aspects of transition * SDT has suggested that environments can support adjustment when they support autonomy, competence and relatedness. * Transition planning has been found to support autonomy through meaningful choice, veteran-led goals, and collaborative decision-making. * Support should provide structure and guidance without becoming unnecessarily controlling, however, it's important to note that providing choices does not automatically satisfy autonomy. === Supporting competence and connection === * Vocational support can help veterans be able to translate military skills into civilian employment and also develop confidence in unfamiliar occupational environments and civilian environments. * Career counselling, feedback, recognition and retraining can strengthen perceived competence. * Services such as peer support, mentoring, family and community involvement can provide opportunities to develop and restore relatedness and belonging. * Effective support should enable veterans to develop new connections whilst allowing them to maintain meaningful military relationships, however, interventions should support multiple psychological needs simultaneously rather than separately. === Implications and limitations === * SDT can provide a framework for evaluating whether reintegration services create conditions that support rather than frustrate needs. * Psychological need satisfaction cannot explain reintegration of broader factors such as housing, finances and access to services. * Therefore, a important research gap is still evidence testing SDT-informed veteran interventions. More longitudinal studies and Australian-specific research should be conducted to determine whether supporting autonomy, competence and relatedness produces a sustained improve in wellbeing and reintegration. ;Embedded links (keeping for reference) * When key words are introduced, use [[Help:Links|interwiki links]] to: ** Wikipedia articles (e.g., "An early psychological view [[w:Dreams|dreams]]) of dreams was provided by [[w:Sigmund Freud|Sigmund Freud]]") or ** Related book chapters (e.g., "If you're feeling stuck, check out the chapter about [[Motivation and emotion/Book/2020/Writer's block|writer's block]]") ==Conclusion== * Military-to-civilian reintegration is a highly complex psychological adjustment that involves changes to identity, daily structure, competence, purpose, relationships and roles. * SDT provides a useful framework to understand how these changes influence autonomy, competence and relatedness, along with the impact upon different types of motivation (autonomous and controlled motivation). * The key finding is that military experiences are not necessarily need-supportive or need-thwarting. Instead, dependent on how leadership, structure, responsibilities and relationships are experienced and understood. * Briefly discuss that identity and purpose are interlinked with the three psychological needs (autonomy, competence and relatedness). * SDT can inform practical interventions by creating transition environments that support identity, choice, competence, connection and meaningful goals. * Important take home message: success reintegration is not solely based on getting veterans into civilian life, instead, it should support veterans in developing self-directed, meaningful and socially connected lives beyond the military service. ==See also== * [[Social connection and emotion regulation|Social Connection]] (Book chapter, 2026)) * [[w:Self determination theory|Self determination theory]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== {{Hanging indent|1= Barnett, A., Savic, M., Lubman, D. (2021). Transitioning to civilian life: The importance of social group engagement and identity among Australian Defence Force veterans. ''Australian and New Zealand Journal of Psychiatry, 56''(8). https://doi.org/10.1177/00048674211046894 Becker, K., Bish, A., Abell, D., McCormack, M., Smidt, M. (2022). Supporting Australian veteran transition: career construction through a person-environment fit perspective. ''The International Journal of Human Resource Management, 36''(5), 799-823. https://doi.org/10.1080/09585192.2022.2077127 Carra, K., Curtin, M., Fortune, T., Gordon, B. (2022). Service and demographic factors, health, trauma exposure, and participation are associated with adjustment for former Australian Defence Force members. ''Military Psychology, 35''(5), 480-492. https://doi.org/10.1080/08995605.2022.2120312 Flack, M., Kite, L. (2021). Transition from military service to civilian: identity, social connectedness, and veteran wellbeing. ''PLoS ONE, 16''(12). https://doi.org/10.1371/journal.pone.0261634 Grimell, J. (2024). You can take a person out of the military, but you can't take the military out of the person: findings from a ten-year identity study on transition from military to civilian life. ''Frontiers in Sociology, 9.'' https://doi.org/10.3389/fsoc.2024.1406710 Kerr, N., Lane, S., Plotnikoff, R., Ashby, S. (2023). The "Transition" to civilian life from the perspective of former serving Australian Defence Force members. ''Journal of Veteran Studies, 9''(1), 129-142. https://10.21061/jvs.v9i1.407 {{ic|fix link}} Knevelsrud, H.C., Sorlie, H., Valaker, S. (2023). Mission command: A self determination theory perspective. ''Military Psychology, 36''(6), 672-688. https://doi.org/10.1080/08995605.2023.2252718 Linden, A., Borjesson, M. (2026). Motivation in physically demanding military roles: a qualitative study using self-determination theory. ''Military Psychology,'' 1-14. https://doi.org/10.1080/08995605.2026.2671587 Loverre, M., Chirico, A., Cinque, L., Palombi, T., Alivernini, F., Lucidi, F., Alessandri, G., Livi, S. (2024). A systematic review of self-determination theory's application in military and police organisations. ''Journal of Police and Criminal Psychology, 40''(5), 685-707. https://doi.org/10.1007/s11896-024-09718-2 Mobbs, M., Bonanno, G. (2018). Beyond war and PTSD: The crucial role of transition stress in the lives of military veterans. ''Clinical Psychology Review, 59,'' 137-144. https://doi.org/10.1016/j.cpr.2017.11.007 Olafsen, A., Halvari, H., Frolound, C. (2021). The basic psychological need satisfaction and need frustration at work scale: A validation study. ''Organisational Psychology, 12.'' https://doi.org/10.3389/fpsyg.2021.697306 Romaniuk, M., Saunders-Dow, E., Brown, K., Batterham, P. (2024). Feasibility, acceptability, and initial outcomes of a psychological adjustment and reintegration program for transitioned military veterans. ''BMC Psychology, 12''(1). https://doi.org/10.1186/s40359-024-02097-7 Ryan, R., Deci, E. (2022). Self determination theory. ''Encyclopedia of quality of life and well-being research.'' https://doi.org/10.1007/978-3-319-69909-7_2630-2 Rybakovaite. J., Poskus, M., Blue, S. (2021). Forced or free choice: Hardiness, need satisfaction, and engagement among military conscripts. ''Current Psychology, 42''(1), 7909-7919. https://doi.org/10.1007/s12144-021-02123-6 Tillberg, L., Truusa, T.T, Tillberg, P. (2026). The skillful veteran: Transforming overseas experience into competence, from the military to civilian working life domain. ''Vocations and Learning, 19''(5). https://doi.org/10.1007/s12186-026-09385-w }} APA style example: {{Hanging indent|1= Rosenberg, B. D., & Siegel, J. T. (2018). A 50-year review of psychological reactance theory: Do not read this article. ''Motivation Science'', ''4''(4), 281–300. https://doi.org/10.1037/mot0000091 Sacks, O. (1985). ''The man who mistook his wife for a hat and other clinical tales''. Harper & Row. }} {{tip|Suggestions for this section: * Wrap the set of references in the [[Template:Hanging indent|hanging indent template]]: ** Use "Edit source" ** <nowiki>{{Hanging indent|1= the full list of references}}</nowiki> * Important aspects of APA referencing style ** Author surname, followed by a comma, then the author initials separated by full stops and spaces ** Year of publication in parentheses ** Title of work in lower case (except first letter and proper names), ending in a full-stop ** Journal title in italics, volume number in italics, issue number in parentheses, first and last page numbers separated by an en-dash(–), followed by a full-stop ** doi as a URL which is a working hyperlink (i.e., clickable) * The most common mistakes include: ** Incorrect capitalisation ** Incorrect italicisation ** dois which aren't clickable as working hyperlinks ** Citing sources that haven't been consulted }} ==External links== Provide [[Help:Contents/Links#External_links|external links]] to highly relevant resources such as podcasts and videos, news articles, and professional sites. Use [[w:Letter case#Sentence casing|sentence casing]] and alphabetical order. For example: * [https://defenceveteransuicide.royalcommission.gov.au/publications/final-report Military-to-civilian Transition Final Report] (Royal Commission) {{tip|Suggestions for this section: * Only select links to major external resources about the topic * Include the source in parentheses after the link }} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Self-determination theory]] [[Category:Motivation and emotion/Book/Veterans]] 8ok1t5uwyv2c7jkdg0pl51rulg82zb8 0 331149 2835402 2835265 2026-10-02T00:31:32Z U3254168 3106320 /* Empathy-altruism hypothesis */ 2835402 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 90cx6wij44b19x6d1odmodzr4cvk6dy 2835403 2835402 2026-10-02T00:40:30Z U3254168 3106320 /* Empathy with victims */ 2835403 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] j7efs1ytmi56nk1yg789a9sk1h6xq2o 2835404 2835403 2026-10-02T00:42:08Z U3254168 3106320 /* Empathy with victims */ 2835404 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]].<quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] t6vqsy61h4btey4g1epb1q4sgvlgz2r 2835405 2835404 2026-10-02T01:08:52Z U3254168 3106320 /* Empathy */ 2835405 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). Kahhale et al. (2026) proposed that individual differences influence how much empathy a person feels or can feel. In line with this, Garvey (2000) proposed empathy as a [[wiktionary:character_trait|character trait]]. <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 6igwd0xxx9qcscyy78mmbc81w3t8gjr 2835406 2835405 2026-10-02T01:23:37Z U3254168 3106320 /* Empathy */ 2835406 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 6h09xlm7388ef0hqb9gup5r43cpxmhk 2835407 2835406 2026-10-02T01:26:42Z U3254168 3106320 /* Empathy */ 2835407 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the Ultimatum Game, which was originally proposed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] esyo0vmgkgxfpcuy57mrx29pl5uk5sd 2835408 2835407 2026-10-02T01:28:05Z U3254168 3106320 /* Empathy-altruism hypothesis */ 2835408 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] sq8m54eqsn2i8vtujvah3nkrwsgiog0 2835410 2835408 2026-10-02T01:36:42Z U3254168 3106320 /* Empathy */ 2835410 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] cpwz7crk8v2f801dcdhh35w3jl9miny 2835413 2835410 2026-10-02T01:46:31Z U3254168 3106320 /* Empathy */ 2835413 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of possible questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 3papktjuadk2act2mpwfc5yso2h5sq1 2835414 2835413 2026-10-02T01:47:01Z U3254168 3106320 /* Empathy */ 2835414 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between emotion display, identity and behaviour in that people use evaluation, potency and activity to interpret identities (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 4ps3njnwupw10n13mr7jav8n1z65jof 2835415 2835414 2026-10-02T01:47:55Z U3254168 3106320 /* Affect control theory */ 2835415 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] bnbejgl6ew4a9gggfo1b72ei6k686ew 2835416 2835415 2026-10-02T01:56:24Z U3254168 3106320 /* References */ 2835416 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. Journal of Experimental Social Psychology, 13(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] amaniuxynp7kicpqufir48o9agzo8sv 2835418 2835416 2026-10-02T02:07:07Z U3254168 3106320 /* References */ 2835418 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Jurors only.{{expand}}]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 8hw2fg5mrevcczsuneda1cabzgdo6dp 2835419 2835418 2026-10-02T02:27:49Z U3254168 3106320 /* Overview */ 2835419 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] gtlhljv56jv5udiwutdskxok2utf1rg 2835426 2835419 2026-10-02T03:09:43Z U3254168 3106320 /* Emotional reasoning */ 2835426 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As stated throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] jtu84tz7i2fibfhsjv3oe91yi3kvukx 2835438 2835426 2026-10-02T03:33:03Z U3254168 3106320 /* Affect control theory */ 2835438 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As stated throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|Affect control theory with empathy variable]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] ryyat00dckzof8o35yzjqt9ike2ns5f 2835440 2835438 2026-10-02T03:34:18Z U3254168 3106320 /* Affect control theory */ 2835440 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] jy9tqgy9iayx921ohx482zrq29rz6nz 2835441 2835440 2026-10-02T03:35:37Z U3254168 3106320 /* Affect control theory */ 2835441 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|400px|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] bsl8vedxrpkwns7e07yklimv76p92fq 2835442 2835441 2026-10-02T03:35:59Z U3254168 3106320 /* Affect control theory */ 2835442 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]] * Jurors are more likely to feel empathy towards people that they like and people who are like them (Phalen et al., 2025). * Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). * Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|800px|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] o4qk6v2hzlq87nkd3fno6ddldamytmd 2835443 2835442 2026-10-02T03:37:02Z U3254168 3106320 /* Emotional reasoning */ 2835443 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]]Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). However, Phalen et a. (2025) found that jurors are more likely to feel empathy towards people who they like and people who are like them. Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|800px|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== {{ic|Include source in parentheses after the link}} * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 1553bi0xlfddzy4i9nbvpokfnakbk14 2835444 2835443 2026-10-02T03:38:17Z U3254168 3106320 /* External links */ 2835444 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]]Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). However, Phalen et a. (2025) found that jurors are more likely to feel empathy towards people who they like and people who are like them. Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|800px|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. It is unclear whether victim impact statements influence empathy and sentencing (Kahhale et al., 2026; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] (YouTube, 2020). * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] (YouTube, 2021). [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] sl59uedoq3ylems8fvwi6m9agohkaqp 2835450 2835444 2026-10-02T03:44:18Z U3254168 3106320 /* Conclusion */ 2835450 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]]Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). However, Phalen et a. (2025) found that jurors are more likely to feel empathy towards people who they like and people who are like them. Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|800px|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. Consistent with this, there is more research on empathy with defendants than there is on empathy with victims (Newman, 1995). It is unclear whether victim impact statements influence empathy and sentencing (Defour et al., 2023; Kahhale et al., 2026; Kunst et al; 2021; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). This may be explained by attribution theory and the empathy-altruism hypothesis (Gould & Sigall, 1977; Zhang et al., 2025). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Affect control theory posits that jurors make decisions by evaluating a defendants emotional display through levels of empathy, evaluation, potency and activity to determine a positive or negative identity. Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] (YouTube, 2020). * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] (YouTube, 2021). [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 53risjvo12z91t23z8tculjlb9pjgfj 2835452 2835450 2026-10-02T03:47:44Z U3254168 3106320 /* Overview */ 2835452 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this impacts jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]]Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). However, Phalen et a. (2025) found that jurors are more likely to feel empathy towards people who they like and people who are like them. Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|800px|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. Consistent with this, there is more research on empathy with defendants than there is on empathy with victims (Newman, 1995). It is unclear whether victim impact statements influence empathy and sentencing (Defour et al., 2023; Kahhale et al., 2026; Kunst et al; 2021; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). This may be explained by attribution theory and the empathy-altruism hypothesis (Gould & Sigall, 1977; Zhang et al., 2025). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Affect control theory posits that jurors make decisions by evaluating a defendants emotional display through levels of empathy, evaluation, potency and activity to determine a positive or negative identity. Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] (YouTube, 2020). * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] (YouTube, 2021). [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] mirp7mr2su2pa0458lbljl80046n43z 2835453 2835452 2026-10-02T03:49:33Z U3254168 3106320 /* See also */ 2835453 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty. The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this impacts jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]]Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). However, Phalen et a. (2025) found that jurors are more likely to feel empathy towards people who they like and people who are like them. Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|800px|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. Consistent with this, there is more research on empathy with defendants than there is on empathy with victims (Newman, 1995). It is unclear whether victim impact statements influence empathy and sentencing (Defour et al., 2023; Kahhale et al., 2026; Kunst et al; 2021; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). This may be explained by attribution theory and the empathy-altruism hypothesis (Gould & Sigall, 1977; Zhang et al., 2025). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Affect control theory posits that jurors make decisions by evaluating a defendants emotional display through levels of empathy, evaluation, potency and activity to determine a positive or negative identity. Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) * [[wikipedia:Empathy|Empathy]] (Wikipedia, 2026) * [[wikipedia:Jury|Jury]] (Wikipedia, 2026) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] (YouTube, 2020). * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] (YouTube, 2021). [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] osmya2wq941lzkjfu59wdd81ilgjwh1 2835454 2835453 2026-10-02T03:50:20Z U3254168 3106320 /* Overview */ 2835454 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty (see Figure 1). The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed PTSD and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this impacts jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]]Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). However, Phalen et a. (2025) found that jurors are more likely to feel empathy towards people who they like and people who are like them. Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|800px|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. Consistent with this, there is more research on empathy with defendants than there is on empathy with victims (Newman, 1995). It is unclear whether victim impact statements influence empathy and sentencing (Defour et al., 2023; Kahhale et al., 2026; Kunst et al; 2021; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). This may be explained by attribution theory and the empathy-altruism hypothesis (Gould & Sigall, 1977; Zhang et al., 2025). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Affect control theory posits that jurors make decisions by evaluating a defendants emotional display through levels of empathy, evaluation, potency and activity to determine a positive or negative identity. Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) * [[wikipedia:Empathy|Empathy]] (Wikipedia, 2026) * [[wikipedia:Jury|Jury]] (Wikipedia, 2026) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] (YouTube, 2020). * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] (YouTube, 2021). [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] b0pr8k52z2bhbwj8r5niu5z19yyygdz 2835455 2835454 2026-10-02T03:51:03Z U3254168 3106320 /* Overview */ 2835455 wikitext text/x-wiki {{title|Empathy and jury decision-making:<br>How does empathy toward defendants and victims influence jurors' reasoning and verdict decisions?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Jurors Only (490613967).jpg|right|thumb|150px|'''Figure 1'''. Only jurors are permitted in this room.]] ; Imagine this ... You have been summoned for jury duty (see Figure 1). The defendant is accused of committing armed robbery in the presence of a shopkeeper. During the trial, you are presented with emotional perspectives of both the victim and the defendant. The victim has developed post traumatic stress disorder and is unable to return to work. The defendant had a traumatic childhood where their parents put immense pressure on them to continue the generational life of crime. Which will have a stronger impact on you? {{RoundBoxBottom}} This chapter discusses the influence of empathy, both towards [[wikipedia:Jury|jurors]] and victims and how this influences jurors' reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this impacts jurors' neutrality in the courtroom (Sjöberg, 2015). Understanding the psychology behind the influence this has on decision-making is essential to ensure that jury trials remain as unbiased as possible. {{RoundBoxTop|theme=3}} '''Focus questions''' * What is empathy? * How does empathy with victims influence jury decision-making? * How does empathy with defendants influence jury decision-making? * How do jurors balance empathy with victims and defendants as well as their role to remain neutral through emotional reasoning? {{RoundBoxBottom}} == Empathy == The term "empathy" was first introduced in the English language by Edward Titchener in 1909, inspired by the German term "Einfühlung" (meaning "feeling into") (Titchener, 1909; Stueber, 2025). Titchener (1909) defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Stueber, 2025). Modern definitions of empathy differ but have in common the ability to feel and understand other's emotional states which typically results in behaving compassionately toward that person (Riess, 2017). There are two types of empathy; trait empathy and state empathy (Wood et al., 2014). Trait empathy is a [[wiktionary:character_trait|character trait]], as proposed by Garvey (2000) and is influenced by individual differences (Kahhale et al., 2026). State empathy is temporary and can be elicited, for example through cross-examination of a defendant or victim impact statements (Haegerich & Bottoms, 2000; Wood et al., 2014). Previous research suggests that high trait empathisers are more likely to give out lesser punishments and hold the defendant less culpable, as well as interpreting regret from the defendant as signs that they are concerned for the victim and are taking personal responsibility (Brooks & Reddon, 2003). In contrast, low trait empathisers are more likely to interpret the defendant's regret as recognition that they have violated norms and as stemming from fear of punishment (Brooks & Reddon, 2003). However, as examining trait empathy in jurors is more difficult than examining state empathy, the majority of research has focused on inducing state empathy in jurors (Plumm & Terrance, 2009). A study by Wood et al. (2014) aimed to understand whether it is trait or state empathy, or a combination of both, which most influences decisions in court cases. The participants were 158 undergraduate students and used an individual mock juror design. Trait empathy was assessed prior to the study using the [[wikipedia:Interpersonal_Reactivity_Index|Interpersonal Reactivity Index]]. The participants were then presented with a booklet with a transcript of the trial, in which the defendant showed no emotion and was found guilty. The control group included neutral opening and closing statements, whereas the experimental group statements were manipulated to induce state empathy. After reading the transcripts, the experimental group wrote a paragraph about how they would feel in the defendant's position, and the control group wrote about what they thought and felt about the case. State empathy with the defendant was then measured, with excellent internal consistency. An example of the type of questions used can be seen at Table 1. The study found that individuals with higher levels of state and/or trait empathy thought the defendant had regret despite the defendant showing no emotion. Those with higher levels of state empathy held the defendant less responsible for the offense. However, only high levels of state empathy, not trait empathy, led to disagreement with the guilty verdict. This suggests that state empathy has more influence in legal judgements than trait empathy (Wood et al., 2014). '''Table 1.''' Likert state empathy scale (adapted from Wood et al., 2014 and Haegerich & Bottoms, 2000). {| class="wikitable" |+ !Item !Scale |- |I can really imagine what the defendant was feeling the night of the crime. |1-7 |- |I have empathy for the defendant. |1-7 |- |I think I have a lot of things in common with the defendant. |1-7 |- |I feel like I can easily take the perspective of the defendant. |1-7 |- |I can experience the same feelings that the defendant experienced. |1-7 |- |I know what it would be like to be the defendant. |1-7 |- |I can really imagine the thoughts running through the defendant's head. |1-7 |} <quiz display="simple"> {Individual differences do not influence empathy: |type="()"} - True + False </quiz> == Empathy with victims == One of the main ways in which jurors empathise with victims is induced is through victim impact statements. Victim impact statements are statements made by the victim or the victim's close family members after a verdict is reached but prior to sentencing where extra details are given. These may include the impact upon the victim and their family; including psychological impact, physical harm, financial losses and social impacts (Alexander, 2019). They are designed to induce empathy in the jurors, in order to give the defendant a harsher sentence (Alexander, 2019; Bandes, 1996). Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). Currently, research on jury decision-making focuses on the guilt deciding phase, rather than the sentencing phase. This means there is little and conflicting evidence upon the impact of victim impact statements on empathy and jury decision-making (Newman, 1995). In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements led to harsher sentencing. Research by Phalen et al. (2021) also supports this notion. However, in studies conducted by Myers & Arbuthnot (1999) and Kahhale et al. (2026) victim impact statements did not influence sentencing. A study by Defour et al. (2023) found inconsistent results. A systematic review by Kunst et al. (2021) examined 36 studies conducted which examined whether victim impact statements had the potential to bias decision-making in jurors and judges. They found inconclusive evidence, which supports the inconsistent findings of the studies above and suggests that more research is required to draw definite conclusions (Kunst et al., 2021). Despite inconsistent findings of the impact of victim impact statements, there is evidence that having similar lived experiences to victims, such as sexual abuse, leads to higher empathy and harsher sentencing (Kahhale et al., 2026). Jurors are also more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). This could be explained by simulation theory, which posits that empathy involves replicating a person's experience in ones mind (Bohlin, 2013). However, there are little available studies linking simulation theory to jury empathy and decision-making. <quiz display="simple"> {Evidence clearly shows that victim impact statements influence empathy: |type="()"} - True + False </quiz> == Empathy with defendants == When jurors have higher levels of empathy with defendants, they are more likely to hand down more lenient verdicts. For example, seminal studies by Garvey (2000) and Sundby (2003) found that jurors who empathised with a defendant were more likely to hand out a life sentence rather than a death sentence. This was reiterated in Sjöberg's (2015) study, which despite finding weaker correlations than the earlier studies, deemed this to be explained by the fact that the study was conducted with a mock jury who did not get much information about the defendant's life and no information about what led the defendant to commit the crime in the first place. Jurors who have empathy with defendants are more likely to consider mitigating factors and associate lower culpability with the defendant (Sjöberg, 2015). In Plumm & Terrance's (2009) study, jurors perceptions of defendants changed when they were presented with empathy inducing statements. Haegerich & Bottoms (2000) found that where empathy was induced in a group of mock jurors, they found the defendant guilty less times than the control group. In fact, 30% of jurors in the first control group went so far as to say that the defendant's traumatic life justified that no punishment be given despite determining they had committed the crime (Haegerich & Bottoms, 2000). === Attribution theory === Haegerich & Bottoms' (2000) findings may be explained by attribution theory. Attribution theory examines the way that people interpret the causes of their behaviours and events, in that they are more likely to link positive outcomes and behaviours to internal attributions, and more likely to link negative outcomes and behaviours to external attributions (Kelley & Michaela, 1980). Gould & Sigall (1977) posit that empathy can modify attributions, which suggests that jurors may be inclined to attribute negative behaviour to external factors, rather than internal factors. This influences juror decision-making as attributions to external factors are more likely to lead to a not-guilty conviction (Gould & Sigall, 1977). Interestingly, when being exposed to both the defendant ''and'' the victim's perspective, the impact of the defendant's perspective was significantly stronger than that of the victim and led to humanisation of the defendant (Kahhale et al., 2026). This may be explained by the empathy-altruism hypothesis (Zhang et al., 2025). === Empathy-altruism hypothesis === The empathy-altruism hypothesis was proposed by Batson et al. (1991) and states that feeling empathy for someone leads to an altruistic desire to help that person. This can be applied to the context of juries in that when empathy with the defendant is induced, jurors are more likely to impose lenient verdicts, which influences the principle of justice due to the development of empathy-based biases in decision-making (Zhang et al., 2025). Zhang et al. (2025) examines this concept in terms of third-party punishers, of which jurors are an example (Son et al., 2019). Zhang et al. (2025) examines the empathy-altruism hypothesis through the lens of the third-party punishment paradigm, which posits that neutral third parties tend to punish defendants to uphold social norms. The study was conducted using the [[wikipedia:Ultimatum_game|Ultimatum Game]], which was originally analysed by Güth et al. (1982). The Ultimatum Game is conducted in pairs, where one player is the proposer and the other is the responder. The proposer is given tokens, of which they have to offer some to the responder and the responder must take it or leave it. If the responder accepts, the tokens are split as the proposer proposed. If the responder rejects, neither player gets anything (Güth et al., 1982). Zhang et al.'s (2025) study was conducted with 31 university students, in a 2 x 2 factorial design, where the variables were empathy vs non-empathy and fair vs unfair. The empathy condition consisted of 'left-behind' students, who were from a remote rural school, whilst the non-empathy condition was made up of normal students from an urban school. The fair variable consisted of an even split of tokens in the Ultimatum Game, where the unfair variable consisted of an uneven split of tokens, and the respondents perception of fairness was measured throughout. The university students observed the Ultimatum Game take place between the proposer and the responder, and the participants received five tokens in each round which could be kept or used to punish the proposer. Zhang et al. (2025) found that the third-party observers were more concerned and emotionally evaluative towards the empathetic proposers, which suggests greater levels of empathy. They also considered the empathetic proposers who made uneven allocations to be more fair than the unempathetic ones. Overall, the study found that third-party punishers decisions of ''whether or not to punish'' are primarily influenced by perceptions of fairness, however the ''decision of the intensity of punishment'' is determined by empathy, consistent with the empathy-altruism hypothesis. This suggests that the empathy-altruism hypothesis is correct in that inducing empathy with defendants can lead to a reduction in the intensity of punishment (Zhang et al., 2025). <quiz display="simple"> {Jurors are more likely to have stronger empathy with the defendant's perspective: |type="()"} + True - False </quiz> == Emotional reasoning == [[File:Balanced justice scale silhouette, small.svg|thumb|'''Figure 2.''' Jurors must balance their emotions and neutrality to come to a decision.]]Empathy shapes how people interpret the evidence presented, determine credibility of witnesses and can influence bias (Sjöberg, 2015). Jurors must balance their emotions with instructions to remain neutral (see Figure 1). However, Phalen et a. (2025) found that jurors are more likely to feel empathy towards people who they like and people who are like them. Empathy can warp the principle of justice by establishing bias towards an individual, which is problematic when one considers that empathy is more likely to be experienced towards people who are familiar, to favour in-group members and further privilege (Decety, 2021). === Affect control theory === Affect control theory (ACT) proposes that there is a relationship between the display of an emotion and the subsequent interpretation of identity and behaviour which occurs through evaluation, potency and activity (Tsoudis, 2002). Evaluation consists of how good or bad a person is, potency consists of how powerful a person is and activity consists of how active or inactive a person is (Tsoudis, 2002). As such, a juror who does not personally know the defendant and the nature of their identity and behaviour would analyse their emotions and the evaluation, potency and activity of them and use their interpretation of the defendant's emotions to judge what kind of person the defendant is and whether this is consistent with the behaviour of the offence (Wood et al., 2014). A defendant who looks sad and remorseful would measure as having a good evaluation, low potency over their actions and inactive, which would lead to an analysis that they have a positive identity (Tsoudis, 2002). Conversely, a defendant who appears happy or smug when hearing about their crimes would have a bad evaluation, high potency and high activity leading to the analysis of a negative identity (Tsoudis, 2002). Tsoudis (2002) argued that empathy should be added as a variable in ACT. As statehow to d throughout this chapter, empathy is an important factor in juror decision-making, which aligns with findings made by Tsoudis (2002). Tsoudis (2002) argues that empathy has previously been viewed as an independent variable in jury decision making, and that by implementing it into ACT, it becomes one of multiple variables impact juror decision making (see Figure 3). [[File:Affect control theory with empathy variable.pdf|thumb|800px|'''Figure 3.''' Affect control theory with empathy variable as modified by Tsoudis (2002).]] <quiz display="simple"> {When empathy establishes bias, it can warp the principle of justice: |type="()"} + True - False </quiz> {{RoundBoxTop|theme=3}} ;Through a practical lens: Autism spectrum disorder Approximately 0.8% of the population has autism spectrum disorder (ASD) (World Health Organisation, 2025). Exact statistics of the amount of autistic people in the criminal justice system is unclear, but is estimated to be between 1%-23% (Chester et al., 2025). This begs the question of whether disclosure of an ASD diagnosis influences empathy in jury members. This has immense practical influence as to whether autistic people are judged fairly by jurors in the criminal justice system. A study by Blackhurst et al. (2022) examined whether disclosure of an ASD diagnosis influenced jury empathy and culpability rates. The study found that disclosure of an ASD diagnosis increased empathy in jurors. Interestingly, the effect of this empathy on decision-making had the biggest influence among people who had a limited understanding of ASD. These people tended to associate lower culpability, perhaps due to stereotypical misconceptions that people with ASD are not responsible for their actions. Contrastingly, people with deeper understandings of ASD were less likely to associate lower culpability due to the presence of ASD, presumably due to an understanding that ASD is a spectrum and does not necessarily mean that autistic people cannot control their behaviours. This provides an interesting perspective on the influence of an ASD diagnosis on jury empathy, and suggests that in cases with autistic defendants, it may be beneficial to educate the jurors on ASD to allow for empathetic consideration without bias. {{RoundBoxBottom}} ==Conclusion== Whilst jurors can feel empathy with both victims and defendants, Kahhale et al. (2026) found that the impact of a defendant's perspective on empathy tends to be significantly stronger than the impact of a victim's perspective. Consistent with this, there is more research on empathy with defendants than there is on empathy with victims (Newman, 1995). It is unclear whether victim impact statements influence empathy and sentencing (Defour et al., 2023; Kahhale et al., 2026; Kunst et al; 2021; Luginbuhl & Burkhad, 1995; Myers & Arbuthnot, 1999; Myers et al., 2002), however having similar experiences to victims and being shown gruesome or graphic images leads to higher rates of empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasise harm suffered and pay less notice to mitigating factors (Bandes, 1996). Jurors who have empathy with defendants are more likely to consider mitigating factors (Sjöberg, 2015), associate lower culpability to the defendant (Haegerich & Bottoms, 2000; Plumm & Terrance, 2009) and hand down more lenient verdicts (Garvey, 2000; Sundby, 2003). This may be explained by attribution theory and the empathy-altruism hypothesis (Gould & Sigall, 1977; Zhang et al., 2025). Jurors are more likely to feel empathy towards people they like who are similar to them (Phalen et al., 2025) and who are in the same in-group as them (Decety, 2021). This can cause bias on how evidence and witnesses are interpreted (Sjöberg, 2015). Empathy is also influenced by individual differences (Kahhale et al., 2026) and can be considered a character trait (Garvey, 2000). Affect control theory posits that jurors make decisions by evaluating a defendants emotional display through levels of empathy, evaluation, potency and activity to determine a positive or negative identity. Empathy clearly impacts juries' decision-making, but empathy for defendants is often stronger than that for victims (Kahhale et al., 2015). This must be considered by the justice system if justice is to be fairly delivered. ==See also== * [[Motivation and emotion/Book/2019/Death penalty motivation|Death penalty motivation]] (Book chapter, 2019) * [[Motivation and emotion/Book/2026/Moral disgust and jury decision-making|Moral disgust and juror decision making]] (Book chapter, 2026) * [[Motivation and emotion/Book/2019/Risky shift motivation|Risky shift motivation]] (Book chapter, 2019) * [[wikipedia:Empathy|Empathy]] (Wikipedia, 2026) * [[wikipedia:Jury|Jury]] (Wikipedia, 2026) ==References== {{Hanging indent|1= Alexander, A. E. (2019). Brace for impact: The effects of victim impact evidence and judicial instructions on juror memory distortion and sentencing decisions in capital trials. ''Student Theses, 2'', 1-55. https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=1099&context=jj_etds Bandes, S. A. (1996). Empathy, narrative and victim impact statements. ''University of Chicago Law Review, 63''(2), 361- 412. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1248284 Batson, C. D., Batson, J. G., Slingsby, J. K., Harrell, K. L., Peekna, H. M., & Todd, R. M. (1991). Empathic joy and the empathy-altruism hypothesis. ''Journal of Personality and Social Psychology, 61''(3), 413–426. https://doi.org/10.1037/0022-3514.61.3.413 Blackhurst, T., Hartley, C., Turner, P., & Warmelink, L. (2022). Jurors’ judgements of an autistic defendant are influenced by awareness of autism, knowledge of psychological conditions and trait-empathy. ''Journal of Intellectual Disabilities and Offending Behaviour, 13''(3), 90-101. https://doi.org/10.1108/JIDOB-09-2022-0007 Bohlin, H. (2013). Simulation theory. In: Runehov, A. L. C. & Oviedo, L. (Eds) ''Encyclopedia of Sciences and Religions'' (1st ed., pp. 2146–2153). Springer. https://doi.org/10.1007/978-1-4020-8265-8_906 Bright, D. A., & Goodman-Delahunty, J. (2006). Gruesome evidence and emotion: anger, blame, and jury decision-making. ''Law and human behavior, 30''(2), 183–202. https://doi.org/10.1007/s10979-006-9027-y Brooks, J. H., & Reddon, J. R. (2003). The two dimensional nature of remorse: An empirical inquiry into internal and external aspects. ''Journal of Offender Rehabilitation, 38''(2), 1-15. https://doi.org/10.1300/J076v38n02_01 Chester, V., Melvin, C., Bunning, K., Alexander, R., & Langdon, P. E. (2025). Autistic people within forensic psychiatric services and the criminal justice system: A systematic review. ''The Journal of Forensic Psychiatry & Psychology, 36''(5), 711–773. https://doi.org/10.1080/14789949.2025.2558833 Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. ''Journal of Personality and Social Psychology, 44''(1), 113–126. https://doi.org/10.1037/0022-3514.44.1.113 Decety, J. (2021). Why empathy is not a reliable source of information in moral decision making. ''Current Directions in Psychological Science, 30''(5), 425-430. https://doi.org/10.1177/09637214211031943 Dufour, G. K., Ternes, M., & Stinson, V. (2023). The relationship between victim impact statements and judicial decision making: An archival analysis of sentencing outcomes. ''Law and Human Behaviour, 47''(4), 484-498. https://doi.org/10.1037/lhb0000535?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle Garvey, S. P. (2000). The emotional economy of capital sentencing. ''New York University Law Review, 75''(26), 26-73. https://nyulawreview.org/wp-content/uploads/2018/08/NYULawReview-75-1-Garvey.pdf Gould, R., & Sigall, H. (1977). The effects of empathy and outcome on attribution: An examination of the divergent-perspectives hypothesis. ''Journal of Experimental Social Psychology, 13''(5), 480-491. https://doi.org/10.1016/0022-1031(77)90032-4 Güth, W., Schmittberger, R., & Schwarze, B. (1982). An experimental analysis of ultimatum bargaining. ''Journal of Economic Behaviour and Organisation, 3''(4), 367-388. https://doi.org/10.1016/0167-2681(82)90011-7 Haegerich, T. M., & Bottoms, B. L. (2000). Empathy and jurors' decisions in patricide trials involving child sexual assault allegations. ''Law and Human Behavior, 24''(4), 421–448. https://doi.org/10.1023/A:1005592213294 Jones, T. M., Bottoms, B. L., & Stevenson, M. C. (2020). Child victim empathy mediates the influence of jurors’ sexual abuse experiences on child sexual abuse case judgments: Meta-analyses. ''Psychology, Public Policy, and Law'', ''26''(3), 312–332. https://psycnet.apa.org/doi/10.1037/law0000231 Kahhale, I., Hackel, L., & Zaki, J. (2026). Balancing emotional scales: Empathy and dehumanization in legal contexts. ''Emotion'', ''26''(1), 97–112. https://doi.org/10.1037/emo0001559 Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Annual review of psychology, 31(1), 457-501. Kunst, M., de Groot, G., Meester, J., & van Doorn, J. (2021). The impact of victim impact statements on legal decisions in criminal proceedings: A systematic review of the literature across jurisdictions and decision types. ''Aggression and Violent Behaviour, 56'', e101512. https://doi.org/10.1016/j.avb.2020.101512 Luginbuhl, J. & Burkhead, M. (1995). Victim impact evidence in a capital trial: Encouraging votes for death. ''American Journal of Criminal Justice, 20'', 1-16. https://doi.org/10.1007/BF02886115 Myers, B., & Arbuthnot, J. (1999). The effects of victim impact evidence on the verdicts and sentencing judgments of mock jurors. ''Journal of Offender Rehabilitation, 29''(3–4), 95–112. https://doi.org/10.1300/J076v29n03_05 Newman, D. W. (1995). Jury decision making and the effect of victim impact statements in the penalty phase. ''Criminal Justice Policy Review, 7'' (3-4), 291-300. https://doi.org/10.1177/088740349500700305 Patry, M. W. (2008). Attractive but guilty: Deliberation and the physical attractiveness bias. ''Psychological Reports, 102''(3), 727-733. https://doi.org/10.2466/pr0.102.3.727-733 Phalen, H. J., Bettis, T. C., Bean, S. R., & Salerno, J. M. (2025). Jurymen seldom rule against a person that they like: The relationship between emotions towards a defendant, the understanding of case facts, and juror judgments in civil trials. ''Behavioral Sciences, 15''(7), 965. https://doi.org/10.3390/bs15070965 Phalen, H.J., Salemo, J.M. & Nadler, J. (2021) Emotional evidence in court. In Bandes, S. A., Madeira, J. L., Temple, K. D., White, E. K. (Eds), ''Research Handbook on Law and Emotion'' (pp. 288-311). Edward Elgar Publishing, Plumm, K. M., & Terrance, C. A. (2009). Battered women who kill: The impact of expert testimony and empathy induction in the courtroom. ''Violence Against Women, 15''(2), 186-205. https://doi.org/10.1177/1077801208329145 Riess H. (2017). The science of empathy. ''Journal of Patient Experience, 4''(2), 74–77. https://doi.org/10.1177/2374373517699267 Sjöberg, M. P. (2015). The relationship between empathy and stringency of punishment in mock jurors. ''Journal of European Psychology Students, 6''(1), 37-44. https://doi.org/10.5334/jeps.cr Son, J. Y., Bhandari, A., & FeldmanHall, O. (2019). Crowdsourcing punishment: Individuals reference group preferences to inform their own punitive decisions. ''Scientific Reports, 9''(1), 11625. https://doi.org/10.1038/s41598-019-48050-2 Stueber, K. (2025). Empathy. In In E. N. Zalta & U. Nodelman (Eds.), ''The Stanford Encyclopedia of Philosophy'' (Winter 2025 Edition). https://plato.stanford.edu/archives/win2025/entries/empathy/ Sundbey, S. E., (2003). The capital jury and empathy: The problem of worthy and unworthy victims. ''Cornell Law Review, 88''(2), 343-381. https://scholarship.law.cornell.edu/cgi/viewcontent.cgi?article=2906&context=clr Titchener, E. B., 1909, ''Lectures on the Experimental Psychology of Thought-Processes'', New York: Macmillan. Wood, J. L., James, M., & Ciardha, C. Ó. (2014). 'I know how they must feel': Empathy and judging defendants. ''The European Journal of Psychology Applied to Legal Context, 6'', 37-43. http://dx.doi.org/10.5093/ejpalc2014a5 World Health Organisation. (2025). ''Autism''. https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders Zhang, G., Tan, M., Li, J., & Zhong, Y. (2025). Altruistic or fair? The influence of empathy on third-party punishment: an event-related potential study. ''Social Cognitive and Affective Neuroscience, 20''(1), nsaf042. https://doi.org/10.1093/scan/nsaf042 }} ==External links== * [https://www.youtube.com/watch?v=SmydcWCacTw Jury decision making] (YouTube, 2020). * [https://www.youtube.com/watch?v=F9DqVyM-KyQ What happens during jury deliberation?] (YouTube, 2021). [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] [[Category:Motivation and emotion/Book/Group]] [[Category:Motivation and emotion/Book/Legal]] [[Category:Motivation and emotion/Book/Decision making]] 8enxj2u98e4q1i4qxzqzsy5tfqlzjgz 2 331218 2835429 2835084 2026-10-02T03:14:18Z StretchBeyond 3105744 Assisted Wiki chapter edits 2835429 wikitext text/x-wiki == About Me == I am a military veteran, working to complete a Bachelor of Science in Psychology as part of a lifelong approach to learning. After a military career working with people around the world on a spectrum of operations, I wanted to better understand the human dimension and the science behind what makes us all tick. Along the way, I want to give back to the community where I can. I have an interest in veterans' PTSD, advocacy and international affairs. == Book Chapter == [[File:PTSD.png|thumb|250x250px|'''Figure 1.''' PTSD can have a deep and lasting impact on our emotions.]] I am writing a book chapter titled [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Immersive Therapy for PTSD: How does it work and what are the effects?]] This chapter is an individual student contribution as part of a larger [https://www.canberra.edu.au/ University of Canberra] class effort in 2026 to write a book [[Motivation and emotion/Book]]. The 2026 book extends a Wikiversity book series started in 2010, with over 1,800 online book chapters on how psychological science can improve human lives. The book editor and University psychology unit convener is [[User:Jtneill|Dr. James Neill]] ==== Chapters I am working on: ==== ====== [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Immersive Therapy for PTSD: How does it work and what are the effects?]] ====== ====== [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment/Non-invasive brain stimulation techniques|High-frequency rTMS and 3MDR in the treatment of PTSD: An integrated physiological and clinical review]] ====== {{clear}} == Social Contributions == #'''18 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Defence mechanisms and emotion regulation. Edits at https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FDefence_mechanisms_and_emotion_regulation&diff=2822629&oldid=2763661 # '''18 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Neurodivergence and trauma. Edits at https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FNeurodivergence_and_trauma&diff=2822636&oldid=2812805 # '''19 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Incentive theory of motivation. Edits at<nowiki/>https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FIncentive_theory_of_motivation&diff=2822844&oldid=2814898 # '''19 Aug 26:''' UC Canvas Discussion: Introduced the book chapter intent to the class and welcomed anyone with sim<nowiki/>ilar topics or interests to contribute. I offered the same. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456450 # '''20 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page. [[Talk:Motivation and emotion/Book/2026/Perfectionism and procrastination#Reference material]] # '''20 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page.[[Talk:Motivation and emotion/Book/2026/Irritability#Reference material]] # '''22 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Mental health in astronauts. Edits at [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667 ht]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667 tps://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667] # '''25 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page.[[Talk:Motivation and emotion/Book/2026/Feedback literacy#Reference]] # '''25 Aug 26''': UC Canvas Discussion: Responded to student topic query.[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457190 https://uclearn.canberra.edu.au/courses/201]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457190 43/discussion_topics/457190] # '''26 Aug 26:''' Comment: Supported another Wiki user by providing some external link ideas for a Chapter page.[[Talk:Motivation and emotion/Book/2026/Dark empathy#Reference|Talk]]<nowiki/>[[Talk:Motivation and emotion/Book/2026/Dark empathy#Reference|:Motivation and emotion/Book/2026/Dark empathy#Reference]] # '''26 Aug 26:''' UC Canvas Discussion: Responded to student topic query with data from a Random Game of Dice scenar<nowiki/>io.https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457412 # '''27 Aug 26:''' Wiki thanks and editing conversation: [[User talk:Jtneill#Punctuation change in book title]] # '''28 Aug 26:''' UC Canvas Discussion: Responded to student topic query<nowiki/> https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457809 # '''4 Sep 26:''' Comment: Included creation of graphics for Wiki page.[[c:File:Avoidance_and_Processing_Cycles.png|ht]]<nowiki/>[[c:File:Avoidance_and_Processing_Cycles.png|tps://commons.wikimedia.org/wiki/File:Avoidance_and_Processing_Cycles.png]] # '''4 Sep 26:''' Comment: Assisted other Wiki user by adding a quiz temp<nowiki/>late to their chapter page https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FBuilding_therapeutic_alliance&diff=2831108&oldid=2830050 # '''8 Sep 26:''' Comment: Assisted other Wiki user by adding a quiz temp<nowiki/>late to their chapter page https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2832141&oldid=2831622 # '''9 Sep 26:''' Comment: Assisted another Wiki user by adding a quiz te<nowiki/>mplate to their chapter page<nowiki/>https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FOutdoor_play_and_children%27s_emotional_well-being&diff=2832147&oldid=2828722 # '''9 Sep 26:''' UC Canvas Discussion: Responded to student topic query <nowiki/>https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457888 # '''11 Sep 26:''' UC Canvas Discussion: Chapter word count question - in<nowiki/>cludes great response advice from other contributors on tools and techniques https://uclearn.canberra.edu.au/courses/20143/discussion_topics/461216 # '''14 Sep:''' Comment: Assisted another Wiki user by adding some advice<nowiki/> on prediction error references [[Talk:Motivation and emotion/Book/2026/Fear extinction#Prediction Error and Extinction]] # '''15 Sep 26:''' Correspondence: Email exchange between chapter author <nowiki/>and Professor Vermetten, who is credited with creating the 3MDR therapy and referenced in the chapter. "I have looked at the Wikiversity page and think you are on the right path. You have brought together the concepts of immersion, embodiment, motivation, and trauma-focused treatment in a thoughtful and relevant way." # '''16 Sep 26:''' Grammar and content editing improvements on 2025 chapt<nowiki/>er due to links with PTSD and prediction error ,https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FNeuroscience_of_unexpected_positive_outcomes&diff=2833368&oldid=2762078 # '''16 Sep 26:''' UC Canvas Discussion: Responded to student request for<nowiki/> chapter feedback on impulsivity and sensation seeking https://uclearn.canberra.edu.au/courses/20143/discussion_topics/461607 # '''16 Sep 26:''' UC Canvas Discussion: Responded to student request for<nowiki/> chapter feedback on brain implants for chronic pain<nowiki/>https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457902 # '''17 Sep 26:''' UC Canvas Discussion: Chapter referencing question abo<nowiki/>ut integration of non-academic journal sources neede<nowiki/>d to source financial market analysis relating to immersive PTSD forecasts. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/462166 # '''21 Sep 26:''' Comment: Assisted another Wiki user by making formatti<nowiki/>ng changes in chapter heading styles to create page <nowiki/>menu. https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FHypothalamus_and_homeostatic_motivation&diff=2834144&oldid=2833547 # '''21 Sep 26:''' UC Canvas discussion: Chapter feedback provided on UC <nowiki/>Canvas at the request of the author.[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901 https://uclearn.]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901 canberra.edu.au/courses/20143/discussion_topics/457901] # '''21 Sep 26:''' UC Canvas discussion: Assisted user with search for li<nowiki/>terature. Provided a number of contemporary meta-ana<nowiki/>lyses and systetemic reviews from the library that may help their research. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/459237 # '''23 Sep 26:''' UC Canvas discussion: From combat to cognition - a lay<nowiki/>person's insights into motivation [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 https://uclearn.ca]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 nberra.edu.au/courses/20143/discussion_topics/456345] # '''24 Sep 26:''' UC Canvas discussion: What do you really want to learn<nowiki/> about - Body language and non-verbal communication[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261 h]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261 ttps://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261] # '''25 Sep 26:''' Added sub-page content to consolidate additional readi<nowiki/>ng, learning and research that I have done between P<nowiki/>TSD treatment and physiological psychology involving non-invasive brain stimulation: [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment/Non-invasive brain stimulation techniques]] # '''27 Sep 26:''' Wiki editing of another chapter: [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 https://en.wikiversit]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 y.org/w/index.php?title=Motivation_and_emotion%2FBoo]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 k%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606] # '''27 Sep 26:''' UC Canvas discussion: Chapter feedback provided on UC <nowiki/>Canvas at the request of the author [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/463438 https://uclearn.]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/463438 canberra.edu.au/courses/20143/discussion_topics/463438] # '''28 Sep 26:''' Wiki discussion page - thanked another user for their <nowiki/>excellent, constructive feedback.[[Talk:Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Talk:Motivation and]]<nowiki/> [[Talk:Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|emotion/Book/2026/Immersive therapy for PTSD treatment]] # '''30 Sep 26:''' Wiki grammar improvements to 2025 book chapter. [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 https:]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 //en.wikiversity.org/w/index.php?title=Motivation_an]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 d_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846] # '''2 Oct 26:''' Wiki improvements to 2025 book chapter.[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 https://en.wikiv]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 ersity.org/w/index.php?title=Motivation_and_emotion%]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270] a3lk5bqhriirjl9qm3yzty8mc2xdxdp 2835439 2835429 2026-10-02T03:33:31Z StretchBeyond 3105744 2835439 wikitext text/x-wiki == About Me == I am a military veteran, working to complete a Bachelor of Science in Psychology as part of a lifelong approach to learning. After a military career working with people around the world on a spectrum of operations, I wanted to better understand the human dimension and the science behind what makes us all tick. Along the way, I want to give back to the community where I can. I have an interest in veterans' PTSD, advocacy and international affairs. == Book Chapter == [[File:PTSD.png|thumb|250x250px|'''Figure 1.''' PTSD can have a deep and lasting impact on our emotions.]] I am writing a book chapter titled [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Immersive Therapy for PTSD: How does it work and what are the effects?]] This chapter is an individual student contribution as part of a larger [https://www.canberra.edu.au/ University of Canberra] class effort in 2026 to write a book [[Motivation and emotion/Book]]. The 2026 book extends a Wikiversity book series started in 2010, with over 1,800 online book chapters on how psychological science can improve human lives. The book editor and University psychology unit convener is [[User:Jtneill|Dr. James Neill]] ==== Chapters I am working on: ==== ====== [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Immersive Therapy for PTSD: How does it work and what are the effects?]] ====== ====== [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment/Non-invasive brain stimulation techniques|High-frequency rTMS and 3MDR in the treatment of PTSD: An integrated physiological and clinical review]] ====== {{clear}} == Social Contributions == #'''18 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Defence mechanisms and emotion regulation. Edits at https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FDefence_mechanisms_and_emotion_regulation&diff=2822629&oldid=2763661 # '''18 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Neurodivergence and trauma. Edits at https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FNeurodivergence_and_trauma&diff=2822636&oldid=2812805 # '''19 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Incentive theory of motivation. Edits at<nowiki/>https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FIncentive_theory_of_motivation&diff=2822844&oldid=2814898 # '''19 Aug 26:''' UC Canvas Discussion: Introduced the book chapter intent to the class and welcomed anyone with sim<nowiki/>ilar topics or interests to contribute. I offered the same. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456450 # '''20 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page. [[Talk:Motivation and emotion/Book/2026/Perfectionism and procrastination#Reference material]] # '''20 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page.[[Talk:Motivation and emotion/Book/2026/Irritability#Reference material]] # '''22 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Mental health in astronauts. Edits at [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667 ht]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667 tps://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667] # '''25 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page.[[Talk:Motivation and emotion/Book/2026/Feedback literacy#Reference]] # '''25 Aug 26''': UC Canvas Discussion: Responded to student topic query.[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457190 https://uclearn.canberra.edu.au/courses/201]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457190 43/discussion_topics/457190] # '''26 Aug 26:''' Comment: Supported another Wiki user by providing some external link ideas for a Chapter page.[[Talk:Motivation and emotion/Book/2026/Dark empathy#Reference|Talk]]<nowiki/>[[Talk:Motivation and emotion/Book/2026/Dark empathy#Reference|:Motivation and emotion/Book/2026/Dark empathy#Reference]] # '''26 Aug 26:''' UC Canvas Discussion: Responded to student topic query with data from a Random Game of Dice scenar<nowiki/>io.https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457412 # '''27 Aug 26:''' Wiki thanks and editing conversation: [[User talk:Jtneill#Punctuation change in book title]] # '''28 Aug 26:''' UC Canvas Discussion: Responded to student topic query<nowiki/> https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457809 # '''4 Sep 26:''' Comment: Included creation of graphics for Wiki page.[[c:File:Avoidance_and_Processing_Cycles.png|ht]]<nowiki/>[[c:File:Avoidance_and_Processing_Cycles.png|tps://commons.wikimedia.org/wiki/File:Avoidance_and_Processing_Cycles.png]] # '''4 Sep 26:''' Comment: Assisted other Wiki user by adding a quiz temp<nowiki/>late to their chapter page https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FBuilding_therapeutic_alliance&diff=2831108&oldid=2830050 # '''8 Sep 26:''' Comment: Assisted other Wiki user by adding a quiz temp<nowiki/>late to their chapter page https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2832141&oldid=2831622 # '''9 Sep 26:''' Comment: Assisted another Wiki user by adding a quiz te<nowiki/>mplate to their chapter page<nowiki/>https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FOutdoor_play_and_children%27s_emotional_well-being&diff=2832147&oldid=2828722 # '''9 Sep 26:''' UC Canvas Discussion: Responded to student topic query <nowiki/>https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457888 # '''11 Sep 26:''' UC Canvas Discussion: Chapter word count question - in<nowiki/>cludes great response advice from other contributors on tools and techniques https://uclearn.canberra.edu.au/courses/20143/discussion_topics/461216 # '''14 Sep:''' Comment: Assisted another Wiki user by adding some advice<nowiki/> on prediction error references [[Talk:Motivation and emotion/Book/2026/Fear extinction#Prediction Error and Extinction]] # '''15 Sep 26:''' Correspondence: Email exchange between chapter author <nowiki/>and Professor Vermetten, who is credited with creating the 3MDR therapy and referenced in the chapter. "I have looked at the Wikiversity page and think you are on the right path. You have brought together the concepts of immersion, embodiment, motivation, and trauma-focused treatment in a thoughtful and relevant way." # '''16 Sep 26:''' Grammar and content editing improvements on 2025 chapt<nowiki/>er due to links with PTSD and prediction error ,https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FNeuroscience_of_unexpected_positive_outcomes&diff=2833368&oldid=2762078 # '''16 Sep 26:''' UC Canvas Discussion: Responded to student request for<nowiki/> chapter feedback on impulsivity and sensation seeking https://uclearn.canberra.edu.au/courses/20143/discussion_topics/461607 # '''16 Sep 26:''' UC Canvas Discussion: Responded to student request for<nowiki/> chapter feedback on brain implants for chronic pain<nowiki/>https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457902 # '''17 Sep 26:''' UC Canvas Discussion: Chapter referencing question abo<nowiki/>ut integration of non-academic journal sources neede<nowiki/>d to source financial market analysis relating to immersive PTSD forecasts. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/462166 # '''21 Sep 26:''' Comment: Assisted another Wiki user by making formatti<nowiki/>ng changes in chapter heading styles to create page <nowiki/>menu. https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FHypothalamus_and_homeostatic_motivation&diff=2834144&oldid=2833547 # '''21 Sep 26:''' UC Canvas discussion: Chapter feedback provided on UC <nowiki/>Canvas at the request of the author.[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901 https://uclearn.]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901 canberra.edu.au/courses/20143/discussion_topics/457901] # '''21 Sep 26:''' UC Canvas discussion: Assisted user with search for li<nowiki/>terature. Provided a number of contemporary meta-ana<nowiki/>lyses and systetemic reviews from the library that may help their research. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/459237 # '''23 Sep 26:''' UC Canvas discussion: From combat to cognition - a lay<nowiki/>person's insights into motivation [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 https://uclearn.ca]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 nberra.edu.au/courses/20143/discussion_topics/456345] # '''24 Sep 26:''' UC Canvas discussion: What do you really want to learn<nowiki/> about - Body language and non-verbal communication[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261 h]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261 ttps://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261] # '''25 Sep 26:''' Added sub-page content to consolidate additional readi<nowiki/>ng, learning and research that I have done between P<nowiki/>TSD treatment and physiological psychology involving non-invasive brain stimulation: [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment/Non-invasive brain stimulation techniques]] # '''27 Sep 26:''' Wiki editing of another chapter: [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 https://en.wikiversit]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 y.org/w/index.php?title=Motivation_and_emotion%2FBoo]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 k%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606] # '''27 Sep 26:''' UC Canvas discussion: Chapter feedback provided on UC <nowiki/>Canvas at the request of the author [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/463438 https://uclearn.]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/463438 canberra.edu.au/courses/20143/discussion_topics/463438] # '''28 Sep 26:''' Wiki discussion page - thanked another user for their <nowiki/>excellent, constructive feedback.[[Talk:Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Talk:Motivation and]]<nowiki/> [[Talk:Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|emotion/Book/2026/Immersive therapy for PTSD treatment]] # '''30 Sep 26:''' Wiki grammar improvements to 2025 book chapter. [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 https:]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 //en.wikiversity.org/w/index.php?title=Motivation_an]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 d_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846] # '''2 Oct 26:''' Wiki improvements to 2025 book chapter.[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 https://en.wikiv]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 ersity.org/w/index.php?title=Motivation_and_emotion%]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270] # '''2 Oct 26:''' UC Canvas discussion - Initiated chapter referencing hi<nowiki/>nts for Wiki editing[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/464585 https://uclearn.canberra.edu.au/]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/464585 courses/20143/discussion_topics/464585] 7tqnp4hhkve8r0qc2444luqggd0z3er 2835446 2835439 2026-10-02T03:41:22Z StretchBeyond 3105744 Added graphic 2835446 wikitext text/x-wiki == About Me == [[File:Stretch-Beyond Company Logo.png|left|thumb|'''Figure 1.''' Stretch Beyond: Strategic insight and psychological resilience for leaders navigating change and complexity.]] I am a military veteran, working to complete a Bachelor of Science in Psychology as part of a lifelong approach to learning. After a military career working with people around the world on a spectrum of operations, I wanted to better understand the human dimension and the science behind what makes us all tick. Along the way, I want to give back to the community where I can. I have an interest in veterans' PTSD, advocacy and international affairs. == Book Chapter == I am writing a book chapter titled [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Immersive Therapy for PTSD: How does it work and what are the effects?]] This chapter is an individual student contribution as part of a larger [https://www.canberra.edu.au/ University of Canberra] class effort in 2026 to write a book [[Motivation and emotion/Book]]. The 2026 book extends a Wikiversity book series started in 2010, with over 1,800 online book chapters on how psychological science can improve human lives.[[File:PTSD.png|thumb|250x250px|'''Figure 2.''' PTSD can have a deep and lasting impact on our emotions.]]The book editor and University psychology unit convener is [[User:Jtneill|Dr. James Neill]] ==== Chapters I am working on: ==== ====== [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Immersive Therapy for PTSD: How does it work and what are the effects?]] ====== ====== [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment/Non-invasive brain stimulation techniques|High-frequency rTMS and 3MDR in the treatment of PTSD: An integrated physiological and clinical review]] ====== {{clear}} == Social Contributions == #'''18 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Defence mechanisms and emotion regulation. Edits at https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FDefence_mechanisms_and_emotion_regulation&diff=2822629&oldid=2763661 # '''18 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Neurodivergence and trauma. Edits at https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FNeurodivergence_and_trauma&diff=2822636&oldid=2812805 # '''19 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Incentive theory of motivation. Edits at<nowiki/>https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FIncentive_theory_of_motivation&diff=2822844&oldid=2814898 # '''19 Aug 26:''' UC Canvas Discussion: Introduced the book chapter intent to the class and welcomed anyone with sim<nowiki/>ilar topics or interests to contribute. I offered the same. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456450 # '''20 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page. [[Talk:Motivation and emotion/Book/2026/Perfectionism and procrastination#Reference material]] # '''20 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page.[[Talk:Motivation and emotion/Book/2026/Irritability#Reference material]] # '''22 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Mental health in astronauts. Edits at [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667 ht]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667 tps://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667] # '''25 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page.[[Talk:Motivation and emotion/Book/2026/Feedback literacy#Reference]] # '''25 Aug 26''': UC Canvas Discussion: Responded to student topic query.[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457190 https://uclearn.canberra.edu.au/courses/201]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457190 43/discussion_topics/457190] # '''26 Aug 26:''' Comment: Supported another Wiki user by providing some external link ideas for a Chapter page.[[Talk:Motivation and emotion/Book/2026/Dark empathy#Reference|Talk]]<nowiki/>[[Talk:Motivation and emotion/Book/2026/Dark empathy#Reference|:Motivation and emotion/Book/2026/Dark empathy#Reference]] # '''26 Aug 26:''' UC Canvas Discussion: Responded to student topic query with data from a Random Game of Dice scenar<nowiki/>io.https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457412 # '''27 Aug 26:''' Wiki thanks and editing conversation: [[User talk:Jtneill#Punctuation change in book title]] # '''28 Aug 26:''' UC Canvas Discussion: Responded to student topic query<nowiki/> https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457809 # '''4 Sep 26:''' Comment: Included creation of graphics for Wiki page.[[c:File:Avoidance_and_Processing_Cycles.png|ht]]<nowiki/>[[c:File:Avoidance_and_Processing_Cycles.png|tps://commons.wikimedia.org/wiki/File:Avoidance_and_Processing_Cycles.png]] # '''4 Sep 26:''' Comment: Assisted other Wiki user by adding a quiz temp<nowiki/>late to their chapter page https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FBuilding_therapeutic_alliance&diff=2831108&oldid=2830050 # '''8 Sep 26:''' Comment: Assisted other Wiki user by adding a quiz temp<nowiki/>late to their chapter page https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2832141&oldid=2831622 # '''9 Sep 26:''' Comment: Assisted another Wiki user by adding a quiz te<nowiki/>mplate to their chapter page<nowiki/>https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FOutdoor_play_and_children%27s_emotional_well-being&diff=2832147&oldid=2828722 # '''9 Sep 26:''' UC Canvas Discussion: Responded to student topic query <nowiki/>https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457888 # '''11 Sep 26:''' UC Canvas Discussion: Chapter word count question - in<nowiki/>cludes great response advice from other contributors on tools and techniques https://uclearn.canberra.edu.au/courses/20143/discussion_topics/461216 # '''14 Sep:''' Comment: Assisted another Wiki user by adding some advice<nowiki/> on prediction error references [[Talk:Motivation and emotion/Book/2026/Fear extinction#Prediction Error and Extinction]] # '''15 Sep 26:''' Correspondence: Email exchange between chapter author <nowiki/>and Professor Vermetten, who is credited with creating the 3MDR therapy and referenced in the chapter. "I have looked at the Wikiversity page and think you are on the right path. You have brought together the concepts of immersion, embodiment, motivation, and trauma-focused treatment in a thoughtful and relevant way." # '''16 Sep 26:''' Grammar and content editing improvements on 2025 chapt<nowiki/>er due to links with PTSD and prediction error ,https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FNeuroscience_of_unexpected_positive_outcomes&diff=2833368&oldid=2762078 # '''16 Sep 26:''' UC Canvas Discussion: Responded to student request for<nowiki/> chapter feedback on impulsivity and sensation seeking https://uclearn.canberra.edu.au/courses/20143/discussion_topics/461607 # '''16 Sep 26:''' UC Canvas Discussion: Responded to student request for<nowiki/> chapter feedback on brain implants for chronic pain<nowiki/>https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457902 # '''17 Sep 26:''' UC Canvas Discussion: Chapter referencing question abo<nowiki/>ut integration of non-academic journal sources neede<nowiki/>d to source financial market analysis relating to immersive PTSD forecasts. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/462166 # '''21 Sep 26:''' Comment: Assisted another Wiki user by making formatti<nowiki/>ng changes in chapter heading styles to create page <nowiki/>menu. https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FHypothalamus_and_homeostatic_motivation&diff=2834144&oldid=2833547 # '''21 Sep 26:''' UC Canvas discussion: Chapter feedback provided on UC <nowiki/>Canvas at the request of the author.[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901 https://uclearn.]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901 canberra.edu.au/courses/20143/discussion_topics/457901] # '''21 Sep 26:''' UC Canvas discussion: Assisted user with search for li<nowiki/>terature. Provided a number of contemporary meta-ana<nowiki/>lyses and systetemic reviews from the library that may help their research. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/459237 # '''23 Sep 26:''' UC Canvas discussion: From combat to cognition - a lay<nowiki/>person's insights into motivation [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 https://uclearn.ca]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 nberra.edu.au/courses/20143/discussion_topics/456345] # '''24 Sep 26:''' UC Canvas discussion: What do you really want to learn<nowiki/> about - Body language and non-verbal communication[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261 h]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261 ttps://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261] # '''25 Sep 26:''' Added sub-page content to consolidate additional readi<nowiki/>ng, learning and research that I have done between P<nowiki/>TSD treatment and physiological psychology involving non-invasive brain stimulation: [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment/Non-invasive brain stimulation techniques]] # '''27 Sep 26:''' Wiki editing of another chapter: [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 https://en.wikiversit]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 y.org/w/index.php?title=Motivation_and_emotion%2FBoo]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 k%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606] # '''27 Sep 26:''' UC Canvas discussion: Chapter feedback provided on UC <nowiki/>Canvas at the request of the author [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/463438 https://uclearn.]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/463438 canberra.edu.au/courses/20143/discussion_topics/463438] # '''28 Sep 26:''' Wiki discussion page - thanked another user for their <nowiki/>excellent, constructive feedback.[[Talk:Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Talk:Motivation and]]<nowiki/> [[Talk:Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|emotion/Book/2026/Immersive therapy for PTSD treatment]] # '''30 Sep 26:''' Wiki grammar improvements to 2025 book chapter. [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 https:]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 //en.wikiversity.org/w/index.php?title=Motivation_an]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 d_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846] # '''2 Oct 26:''' Wiki improvements to 2025 book chapter.[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 https://en.wikiv]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 ersity.org/w/index.php?title=Motivation_and_emotion%]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270] # '''2 Oct 26:''' UC Canvas discussion - Initiated chapter referencing hi<nowiki/>nts for Wiki editing[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/464585 https://uclearn.canberra.edu.au/]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/464585 courses/20143/discussion_topics/464585] l6wscs24r1am7wiibiaygowb9m3e4uc 2835449 2835446 2026-10-02T03:44:08Z StretchBeyond 3105744 Format corrections and layout. 2835449 wikitext text/x-wiki == About Me == [[File:Stretch-Beyond Company Logo.png|thumb|'''Figure 1.''' Stretch Beyond: Strategic insight and psychological resilience for leaders navigating change and complexity.]] I am a military veteran, working to complete a Bachelor of Science in Psychology as part of a lifelong approach to learning. After a military career working with people around the world on a spectrum of operations, I wanted to better understand the human dimension and the science behind what makes us all tick. Along the way, I want to give back to the community where I can. I have an interest in veterans' PTSD, advocacy and international affairs. == Book Chapter == I am writing a book chapter titled [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Immersive Therapy for PTSD: How does it work and what are the effects?]] This chapter is an individual student contribution as part of a larger [https://www.canberra.edu.au/ University of Canberra] class effort in 2026 to write a book [[Motivation and emotion/Book]]. The 2026 book extends a Wikiversity book series started in 2010, with over 1,800 online book chapters on how psychological science can improve human lives. The book editor and University psychology unit convener is [[User:Jtneill|Dr. James Neill]][[File:PTSD.png|thumb|250x250px|'''Figure 2.''' PTSD can have a deep and lasting impact on our emotions.|left]] ==== Chapters I am working on: ==== ====== [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Immersive Therapy for PTSD: How does it work and what are the effects?]] ====== ====== [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment/Non-invasive brain stimulation techniques|High-frequency rTMS and 3MDR in the treatment of PTSD: An integrated physiological and clinical review]] ====== {{clear}} == Social Contributions == #'''18 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Defence mechanisms and emotion regulation. Edits at https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FDefence_mechanisms_and_emotion_regulation&diff=2822629&oldid=2763661 # '''18 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Neurodivergence and trauma. Edits at https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FNeurodivergence_and_trauma&diff=2822636&oldid=2812805 # '''19 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Incentive theory of motivation. Edits at<nowiki/>https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FIncentive_theory_of_motivation&diff=2822844&oldid=2814898 # '''19 Aug 26:''' UC Canvas Discussion: Introduced the book chapter intent to the class and welcomed anyone with sim<nowiki/>ilar topics or interests to contribute. I offered the same. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456450 # '''20 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page. [[Talk:Motivation and emotion/Book/2026/Perfectionism and procrastination#Reference material]] # '''20 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page.[[Talk:Motivation and emotion/Book/2026/Irritability#Reference material]] # '''22 Aug 26:''' Grammar and content editing improvements on 2025 chapter, Mental health in astronauts. Edits at [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667 ht]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667 tps://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FMental_health_in_astronauts&diff=2824159&oldid=2804667] # '''25 Aug 26:''' Comment: Supported another Wiki user by providing some peer-reviewed ideas on starter references f<nowiki/>or a Chapter page.[[Talk:Motivation and emotion/Book/2026/Feedback literacy#Reference]] # '''25 Aug 26''': UC Canvas Discussion: Responded to student topic query.[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457190 https://uclearn.canberra.edu.au/courses/201]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457190 43/discussion_topics/457190] # '''26 Aug 26:''' Comment: Supported another Wiki user by providing some external link ideas for a Chapter page.[[Talk:Motivation and emotion/Book/2026/Dark empathy#Reference|Talk]]<nowiki/>[[Talk:Motivation and emotion/Book/2026/Dark empathy#Reference|:Motivation and emotion/Book/2026/Dark empathy#Reference]] # '''26 Aug 26:''' UC Canvas Discussion: Responded to student topic query with data from a Random Game of Dice scenar<nowiki/>io.https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457412 # '''27 Aug 26:''' Wiki thanks and editing conversation: [[User talk:Jtneill#Punctuation change in book title]] # '''28 Aug 26:''' UC Canvas Discussion: Responded to student topic query<nowiki/> https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457809 # '''4 Sep 26:''' Comment: Included creation of graphics for Wiki page.[[c:File:Avoidance_and_Processing_Cycles.png|ht]]<nowiki/>[[c:File:Avoidance_and_Processing_Cycles.png|tps://commons.wikimedia.org/wiki/File:Avoidance_and_Processing_Cycles.png]] # '''4 Sep 26:''' Comment: Assisted other Wiki user by adding a quiz temp<nowiki/>late to their chapter page https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FBuilding_therapeutic_alliance&diff=2831108&oldid=2830050 # '''8 Sep 26:''' Comment: Assisted other Wiki user by adding a quiz temp<nowiki/>late to their chapter page https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2832141&oldid=2831622 # '''9 Sep 26:''' Comment: Assisted another Wiki user by adding a quiz te<nowiki/>mplate to their chapter page<nowiki/>https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FOutdoor_play_and_children%27s_emotional_well-being&diff=2832147&oldid=2828722 # '''9 Sep 26:''' UC Canvas Discussion: Responded to student topic query <nowiki/>https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457888 # '''11 Sep 26:''' UC Canvas Discussion: Chapter word count question - in<nowiki/>cludes great response advice from other contributors on tools and techniques https://uclearn.canberra.edu.au/courses/20143/discussion_topics/461216 # '''14 Sep:''' Comment: Assisted another Wiki user by adding some advice<nowiki/> on prediction error references [[Talk:Motivation and emotion/Book/2026/Fear extinction#Prediction Error and Extinction]] # '''15 Sep 26:''' Correspondence: Email exchange between chapter author <nowiki/>and Professor Vermetten, who is credited with creating the 3MDR therapy and referenced in the chapter. "I have looked at the Wikiversity page and think you are on the right path. You have brought together the concepts of immersion, embodiment, motivation, and trauma-focused treatment in a thoughtful and relevant way." # '''16 Sep 26:''' Grammar and content editing improvements on 2025 chapt<nowiki/>er due to links with PTSD and prediction error ,https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FNeuroscience_of_unexpected_positive_outcomes&diff=2833368&oldid=2762078 # '''16 Sep 26:''' UC Canvas Discussion: Responded to student request for<nowiki/> chapter feedback on impulsivity and sensation seeking https://uclearn.canberra.edu.au/courses/20143/discussion_topics/461607 # '''16 Sep 26:''' UC Canvas Discussion: Responded to student request for<nowiki/> chapter feedback on brain implants for chronic pain<nowiki/>https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457902 # '''17 Sep 26:''' UC Canvas Discussion: Chapter referencing question abo<nowiki/>ut integration of non-academic journal sources neede<nowiki/>d to source financial market analysis relating to immersive PTSD forecasts. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/462166 # '''21 Sep 26:''' Comment: Assisted another Wiki user by making formatti<nowiki/>ng changes in chapter heading styles to create page <nowiki/>menu. https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FHypothalamus_and_homeostatic_motivation&diff=2834144&oldid=2833547 # '''21 Sep 26:''' UC Canvas discussion: Chapter feedback provided on UC <nowiki/>Canvas at the request of the author.[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901 https://uclearn.]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/457901 canberra.edu.au/courses/20143/discussion_topics/457901] # '''21 Sep 26:''' UC Canvas discussion: Assisted user with search for li<nowiki/>terature. Provided a number of contemporary meta-ana<nowiki/>lyses and systetemic reviews from the library that may help their research. https://uclearn.canberra.edu.au/courses/20143/discussion_topics/459237 # '''23 Sep 26:''' UC Canvas discussion: From combat to cognition - a lay<nowiki/>person's insights into motivation [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 https://uclearn.ca]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 nberra.edu.au/courses/20143/discussion_topics/456345] # '''24 Sep 26:''' UC Canvas discussion: What do you really want to learn<nowiki/> about - Body language and non-verbal communication[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261 h]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261 ttps://uclearn.canberra.edu.au/courses/20143/discussion_topics/455261] # '''25 Sep 26:''' Added sub-page content to consolidate additional readi<nowiki/>ng, learning and research that I have done between P<nowiki/>TSD treatment and physiological psychology involving non-invasive brain stimulation: [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment/Non-invasive brain stimulation techniques]] # '''27 Sep 26:''' Wiki editing of another chapter: [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 https://en.wikiversit]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 y.org/w/index.php?title=Motivation_and_emotion%2FBoo]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606 k%2F2026%2FSelf-concept_and_motivation&diff=2834628&oldid=2834606] # '''27 Sep 26:''' UC Canvas discussion: Chapter feedback provided on UC <nowiki/>Canvas at the request of the author [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/463438 https://uclearn.]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/463438 canberra.edu.au/courses/20143/discussion_topics/463438] # '''28 Sep 26:''' Wiki discussion page - thanked another user for their <nowiki/>excellent, constructive feedback.[[Talk:Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|Talk:Motivation and]]<nowiki/> [[Talk:Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment|emotion/Book/2026/Immersive therapy for PTSD treatment]] # '''30 Sep 26:''' Wiki grammar improvements to 2025 book chapter. [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 https:]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 //en.wikiversity.org/w/index.php?title=Motivation_an]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846 d_emotion%2FBook%2F2025%2FAmygdala_and_fear_motivation&diff=2835083&oldid=2755846] # '''2 Oct 26:''' Wiki improvements to 2025 book chapter.[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 https://en.wikiv]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 ersity.org/w/index.php?title=Motivation_and_emotion%]<nowiki/>[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270 2FBook%2F2026%2FEmotional_intelligence_and_emotional_wellbeing&diff=2835427&oldid=2835270] # '''2 Oct 26:''' UC Canvas discussion - Initiated chapter referencing hi<nowiki/>nts for Wiki editing[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/464585 https://uclearn.canberra.edu.au/]<nowiki/>[https://uclearn.canberra.edu.au/courses/20143/discussion_topics/464585 courses/20143/discussion_topics/464585] skt7s50te2oiukkj5ftptsikg3mhe6i 0 331234 2835492 2834967 2026-10-02T11:03:07Z Mymunu 3106327 /* Children's emotional well-being */ 2835492 wikitext text/x-wiki {{title|Outdoor play and children's emotional well-being:<br>How does outdoor play influence children's emotional well-being?}} __TOC__ == Overview == {| class="wikitable" |'''Case study: Part 1'''[[File:School children happily playing in playground.jpg|thumb|'''Figure 1'''. Children engaged in outdoor play, where social interactions, choice and control on the situation can create different emotional experiences.]]Imagine that... A child arrives at playground and joins a group of children who are already playing. The children are making their own game and deciding the rules as they play. At first, the child enjoys choosing where and what to play. During the game, another child changes the rules of the game and argument breaks out. The child becomes frustrated and walks away from the activity. After watching for a short time, the child returns, suggests a new idea to continue the game and re-joins the group. How might experiences like this during outdoor play influence children's emotional well-being? Emotional regulation provides one psychological framework for understanding how children may respond to situations like this during play (see figure 1). |} Outdoor play can involve more than physical movement. It can occur across playgrounds, gardens, streets and natural spaces. Outdoor play includes exploration, social interaction, choice, challenge, and engagement with the surrounding environment (Dodd et al., 2026; Pereira et al., 2024). As shown in the case study part 1, outdoor play can involve emotional situations such as [[Aggression|frustration]], disagreement, uncertainty or excitement. Gross's (2015) [[emotional regulation]] provides a [[psychological]] explanation for how children may recognise and respond to these emotional situations. Outdoor play experiences are also shaped by the environment where play takes place. Different physical and social environments can provide different opportunities for play, which means the same outdoor space may not provide the same opportunities for every child (Morgenthaler et al., 2024).This chapter examines how [[Emotional regulation|emotional,]] [[Cognitive psychology|cognitive]], social and environmental processes may help explain the relationship between outdoor play and children's [https://w.wiki/AHG6 emotional well-being.] {| class="wikitable" | ;[[File:Bulb Idea Flat Icon GIF Animation.gif|alt=Focus questions|left|99x99px|thumb]] '''Focus questions''' * '''What are outdoor play and children's emotional well-being?''' * '''How does outdoor play influence children's emotional well-being?''' * '''How do social and environmental conditions shape children's outdoor play experiences?''' * '''What does recent research show about outdoor play and children's emotional well-being?''' * '''How can families, communities and schools support outdoor play opportunities that may benefit children's emotional well-being?''' |} == '''Understanding outdoor play and children's emotional well-being''' == [[File:Water-outdoor-people-girl-play-boy-938233.jpg|thumb|'''Figure 2'''. ''Outdoor play can provide opportunities to explore, make choices, interact with others and respond to changing situations through activities such as water play.''|214x214px]] Outdoor play and children's emotional well-being are not measured as single and consistent concepts across recent research. Outdoor play may be examined as voluntary and intrinsically motivated activity, self directed play, parent reported outdoor play, or device-measured outdoor play (Binno et al., 2025; Davenport et al., 2025; Dodd et al., 2026). It should also be distinguished from outdoor moderate-to-vigorous physical activity (MVPA) because these measures do not represent the same behaviour (Davenport et al., 2025). Children's emotional well-being is also examined through different outcomes, which include [https://w.wiki/7YC8 emotional dysregulation], social-emotional competence, positive and negative affect, and internalising or externalising symptoms (Dodd et al., 2026; Ferguson et al., 2025; Lee et al., 2025; Poulos et al., 2026). These differences need to be considered when findings across the studies are compared. === Outdoor play === Outdoor play is voluntary and and intrinsically motivated activity that occurs in outdoor environments such as gardens, playgrounds, parks and natural spaces (Dodd et al., 2026). Free play can be also self-directed, allowing children to interact freely with the environment and have [https://w.wiki/4NyU autonomy] to make choices about their activities (Biino et al., 2025). Outdoor play should not be treated as the same as outdoor physical activity. The recent research outdoor play and outdoor moderate- to-vigorous physical activity (MVPA) were examined as separate measures (Davenport et al., 2025). This distinction is important because outdoor play intensity of physical activity do not represent the same behaviour. === Children's emotional well-being === Children's emotional well-being is not represented by a single common outcome across recent outdoor play research. Emotional dysregulation has been examined in relation to the amount and timing of outdoor play (Lee et al., 2025), while social-emotional competence includes social emotional difficulties and [[Prosocial behavior/Keywords/Definitions|prosocial behaviour]] (Ferguson et al., 2025). Other studies have examined positive and negative affect following recess (Poulos et al., 2026) and trajectories of internalising and externalising symptoms across childhood (Dodd et al., 2026). These outcomes represent different aspects and timeframes of emotional functioning, so they should not be treated as equivalent when findings are compared. '''Table 1''' ''Emotional outcomes examined in recent research on outdoor play and children's emotional well-being'' {| class="wikitable" |+ !Study !Outcome examined !What the outcome represents |- |Lee et al. (2025) |Emotional dysregulation |Difficulties in emotional regulation; examined in relation to the amount of timing of outdoor play |- |Ferguson et al. (2025) |Social-emotional competence |Social-emotional difficulties and prosocial behaviour |- |Poulos et al. (2026) |Positive and negative affect |Children's affect following recess across different settings |- |Dodd et al. (2026) |Internalising and externalising symptoms |Internalising: emotional symptoms and peer problems Externalising: conduct problems and hyperactivity- inattention |} Note. Outcome descriptions are based on the measures and constructs reported in the above cited studies. See Table 1. As shown in Table 1, the studies do not measure the same aspect or time frame of children's emotional functioning. Affect immediately following recess should not be treated as equivalent to emotional dysregulation measured over time or trajectories of internalising and externalising symptoms across childhood. This difference need to be considered when findings across studies are compared. '''Case study: part 2''' ''What is being measured?'' {| class="wikitable" | valign="top" |[[File:Children marbles.jpg|thumb|221x221px|'''Figure 3'''. ''Children's immediate emotional responses during outdoor play is different from long-term emotional functioning.'']]The child in the Case study: Part 1 becomes frustrated when the rules of the game change. This immediate emotional response is different from a longer-term pattern of emotional dysregulation or internalising symptoms. Research on outdoor play measures these outcomes across different time frames and contexts. When findings are compared, it is important to consider which aspect of emotional well-being is measured. {{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {A child's positive or negative affect immediately after recess represents the same emotional outcome as longer-term internalising or externalising symptoms. |type="()"} - True + False </quiz> {{Robelbox/close}} |} == '''How does outdoor play influence children's emotional well-being?''' == Outdoor play may be related to children's emotional well-being through emotional, cognitive, and social processes (Dodd et al., 2026). Possible pathways discussed in the recent research include cognitive, social and emotional skills, social interaction, physical activity, connection with the nature and adventurous play (Dodd et al., 2026). However, these pathways have not all been directly tested as mechanisms, and many of the outdoor play research remain observational (Dodd et al., 2026; de Lannoy et al., 2023). Psychological theory can help to explain how and why outdoor play experiences may influence children's emotional well-being. Although the evidence does not yet show that psychological processes cause the relationship between outdoor play and children's emotional well-being. Emotion involves more than subjective feelings. Scherer (2005) described emotion as coordinated changes across cognitive appraisal, physiological responses, action tendencies, expression and subjective feelings. Therefore, physiological responses are one component of an emotional response rather than a separate explanation for the effects of outdoor play. Scherer (2005) did not examine outdoor play, so this framework does not provide evidence that outdoor play changes children's physiological responses or emotional well-being. === '''Emotion regulation''' === Emotion regulation provides a psychological framework for understanding how children may manage emotional situations during outdoor play. Gross (2015) described emotional regulation as a process involving identification, selection and implementation. Identification concerns deciding whether to regulate an emotion, selection concerns selecting regulation strategy and implementation concerns applying chosen response into practice. Gross (2015) also described situation selection, situation modification, attentional deployment cognitive change and response modulation. During outdoor play, children may experience frustration, conflict, disagreement, uncertainty or changes to their activity. Gross's framework can be applied to these situations to consider how a children recognise an emotional response, choose strategies to manage and act on chosen strategies. However, Gross (2015) did not examine outdoor play, so applying the framework does not show that outdoor play improves children's emotion regulation. Furthermore, research on play provides some association between outdoor play and emotional functioning. Veraksa et al. (2025) systematically reviewed 33 studies on non-therapeutic play among children aged 3 to 7 and identified evidence involving emotional regulation, emotional intelligence, and negative emotional symptoms. The review included outdoor play alongside several other forms of play, so its findings should not be interpreted as evidence that outdoor play alone improves emotion regulation. {| class="wikitable" | valign="top" |'''Case study: Part 3'''[[File:14Y Ncdc july 5th-802.jpg|thumb|202x202px|'''Figure 4'''. ''Children can respond differently to situations that occur during outdoor play.'']]When the rule of game change, the child becomes frustrated and decided to step away. After a short time the child returns and suggests for different way to continue the game (see Figure 4). Suggesting a change to the game can be considered an example of situation modification. This shows how Gross's emotion regulation framework can be applied to an emotional situation during outdoor play. {{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {What does Gross (2015) emotion regulation framework show when it is applied to the outdoor-play scenario?. |type="()"} -A. Outdoor play causes better emotion regulation. +B. Situation modification can help explain how the child responds to the situation. -C. Children regulate emotions better outdoors than indoors. -D. Stepping away from play always improves emotional well-being. </quiz> {{Robelbox/close}} |} === '''Working memory and cognitive process''' === Working memory can be one cognitive process involved in the association between outdoor play and emotional dysregulation. Lee et al., (2025) examined 325 preschool children and tested working memory as a statistical mediator. Outdoor play was examined across three periods of the day; wake up to noon, noon to 6 pm, and 6 pm to bedtime. The findings differed according to the timing of outdoor play. More outdoor play between noon and 6 pm was associated with lower emotional dysregulation. In contrast, more outdoor play before noon and after 6 pm was associated with higher emotional dysfunction. Afternoon outdoor play was also associated with better working memory, and better working memory was associated with lower emotional dysregulation. When working memory was included in the analysis, the association between afternoon outdoor play and emotional dysregulation was no longer statistically significant. Lee et al., (2025) reported this as full mediation. This suggests working memory may be involved in the association between afternoon play and lower emotional dysregulation. However, the study was observational, so the mediation analysis does not show that outdoor play caused better working memory or lower emotional dysregulation. Johnstone et al (2022) reviewed 36 studies of nature-based [[early childhood education]]. The review found very low certainty evidence for some social, emotional, and cognitive outcomes, including [[self-regulation]], while findings for attention were inconsistent. Although, the review examined nature-based early childhood education rather than outdoor play. Therefore, it does not show that working memory explains the association between outdoor play and children's [https://w.wiki/AHG6 emotional well-being]. == '''How does social and environmental conditions influence on children's outdoor play experiences?''' == Outdoor play opportunities depend on the opportunities available in children's social and physical environment. Children may have access to same outdoor space but may not have same opportunities in play. Beekhuizen et al. (2025) identified personal, interacting and environmental factors that could support or restrict inclusive outdoor play. These difference can be considered through [https://w.wiki/VYfL affordance theory], which examines the opportunities for action through the relationship between an individual and the environment (Gibson, 1979). === Affordance theory and outdoor play environments === [https://w.wiki/VYfL Affordance theory] was developed by Gibson (1979) to explain the opportunities for action that environment provides in relation to the person using it. In outdoor play, the opportunities provided by a space can depend on its physical features and how a child is able to use those features. Morgenthaler et al. (2024) applied the affordance theory to children's outdoor play and examined outdoor play transactions and development of an environmental taxonomy of outdoor play space features. Their review identified 14 categories of spaces and 284 play opportunities linked to different environmental features. Morgenthaler et al. (2024) showed that different spaces and objects can afford different forms of play, which means two children using the same outdoor play space may not experience the same play opportunities. Therefore, the theory provides a way of understanding differences between children and their use of an outdoor environment. However this study examined the opportunities for play rather than children's well-being. Pereira et al. (2024) also examined features of outdoor play spaces in a systematic review of 51 articles representing 45 primary studies. The study examined features such as fixed structures, natural elements, floor markings, loose equipment and available play areas. Some positive effects were reported, but there was substantial heterogeneity between studies. The study also differed in the environmental features examined, outcomes measures, and study methods, which made difficult to draw a clear conclusions about the effect of individual play space features (Pereira et al., 2024).Therefore, the review does not show that one particular environmental feature improves children's [https://w.wiki/AHG6 emotional well-being]. '''Table 2'''. ''Examples of environmental features and possible affordances'' {| class="wikitable" |+ !Environmental feature !Possible affordance for play |- |Fixed structures (e.g. climbing frame) |Can provide opportunity in different forms of physical activity. For example, climbing, physical play, risk-taking |- |Natural elements (e.g. tree, rocks, sand) |Environmental features can provide opportunities for exploratory play, imaginative play, sensory experiences |- |Floor markings (e.g. painted games) |Can support structured activities like rule based play, footy, tennis, etc. |- |Loose equipment (e.g. balls, tyre, boxes) |Movable environmental features that can be used during constructive play, imaginative play, creative problem solving play |- |Open play area |Running, group play, or flexible use |} Note. Based on Pereira et al. (2024) and Morgenthaler et al. (2024). Environmental features can afford more than one type of play and the opportunities may vary between children. {| class="wikitable" | valign="top" |'''Case study: Part 4 Same space, different opportunities''' Kim and Leo are both at the same school playground during recess. The playground has climbing feature, sand pit area and open natural space. * Kim quickly joins a group of children in a climbing frame. The climbing frame structure provides him with an opportunity for physical play and social interactions. * Leo uses sand pit area with other child, he plays with loose materials and creates a sand castle and other different structures. The environment gives him an opportunity for imaginative play and social play. Both the examples show how the same outdoor space can afford different forms of play for different children, depending on their interests, skills and social context. {{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {Which statement best applies affordance theory to the example?. |type="()"} -A. The play ground causes children to be more physically active. +B. The same playground can provide different opportunities for play depending on the child and how they use the environment. -C. Climbing structures always lead to better emotional well-being. -D. Open spaces are only useful for social play. </quiz> {{Robelbox/close}} |} === '''Social relationship and inclusion''' === Social relationships can shape whether children are able to join and continue outdoor play (Beekhuizen et al., 2025). Beekhuizen et al. (2025) identified making contact and growing up together as interacting factors in inclusive outdoor play. Familiarity with other children could make it easier to approach, communication and play together, while joining unfamiliar children or existing game could be difficult. Affective social competence provides a psychological framework for understanding these social interactions (Gal-Szabo et al., 2018). Gal-Szabo et al. (2018) described emotional competence as involving experiencing, sending and receiving affect, together with awareness, identification, responding with the social context and regulation. These process may be relevant when a child tries to enter a peer group, recognise other children's emotions and manage their own response during play (Gal-Szabo et al., 2018). Gal-Szabo et al. (2018) also found that situational understanding of the emotions was related to uninvolved behaviour and was marginally related to more social play. However, that the study examined preschool free play rather than specific outdoor play. Beekhuizen et al. (2025) also found that children with disabilities experienced more barriers related to making contact, adapting play and physical play environment. These findings suggest that participation in outdoor play depends on both social interaction and children's ability to respond within the play situation, but they do not establish that social play causes better emotional well-being (Beekhuizen et al., 2025; Gal-Szabo et al., 2018). === '''Autonomy, parents and time''' === Autonomy can shape how children experience outdoor play (Beekhuizen et al., 2025). Beekhuizen et al. (2025) identified autonomy as a personal factor in inclusive outdoor play. Some children valued having independence over what they do and who they play with. Some children with disabilities wanted opportunities to play outside independently without direct parental involvement. Autonomy during play may also have an emotional function. Veraksa et al. (2025), in a systematic review of non-therapeutic play, identified autonomy as one feature through which play may support emotional regulation and coping. However, the review examined several forms of play and does not show that autonomy during outdoor play specially improves children's emotional well-being. Parental support can also make outdoor play possible. Beekhuizen et al. (2025) found that parental involvement could support children's participation when a child needed help to access or participate in outdoor play. Time constraints also affected opportunities for outdoor play. Some children had less time to play outdoors because of parents' work schedule, after school arrangements or longer travel distance between home and school (Beekhuizen et al., 2025). These constraints could limit opportunities for outdoor play even when children wanted greater independence. === '''Outdoor environments and accessibility''' === Outdoor play environment can support or restrict children's participation (Beekhuizen et al., 2025). Their identified both physical and social features of outdoor environments as relevant to inclusive play. Children discussed safety, including traffic near playgrounds and disputes with other children. Accessibility was particularly important for children with disabilities because opportunities for inclusive outdoor play could be affected by play environments and physical abilities. Pereira et al. (2024) also showed that heterogeneity between studies limited clear conclusion about the effects of individual outdoor play space features.. Gibson et al. (2017) reported a similar limitation for loose-parts play. Their systematic review found insufficient quantitative evidence to determine whether loose-parts interventions affected children's cognitive, social or emotional development. Together, these findings show that features of outdoor environments can support or restrict opportunities for play. However, current evidence does not establish a particular environmental feature that improves children's emotional well-being ( Beekhuizen et al., 2025; Gibson et al., 2017; Pereira et al., 2024). {| class="wikitable" | valign="top" |'''Case study: Part 5 Same play space, different experiences''' {| class="wikitable" |Kim and Leo uses the same school playground. Kim already knows many children and easily joins the group activity. Leo uses a mobility device and finds some areas of playground is difficult to access. Leo also does not know many children who are already playing. Leo also prefers to play independently when possible. |} The two children have access to the same playground space, but their opportunities to participate is different. Affordance theory can help to understand how the physical environment provides opportunities depending on child and how the space can be used. Beekhuizen et al. (2025) also identified making contact, familiarity, autonomy and accessibility as factors that could support or restrict inclusive outdoor play. Physical accessibility may affect whether a child can use part of playground, while familiarity with other children may affect whether the child can enter social play. Parental support may also help participation in some situations, while the child may still value greater independence {{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {Why might two children have different outdoor play experiences even they use the same playground?. |type="()"} +A. Physical, social and personal contributions can affect who child are able to participate. -B. Outdoor spaces provide the same opportunities for every child. -C. Accessibility is the only factor that affects outdoor play.. -D. Children who know other children always have better emotional well-being. </quiz> {{Robelbox/close}} |} == '''What does recent research show about outdoor play and children's emotional well-being?''' == Recent research does not claim a consistent association between outdoor play and children's emotional well-being. The findings are mixed across different emotional outcomes being measured, the timing of outdoor play, children's behaviours, and the methods used to measure outdoor play. These differences are significant when interpreting whether outdoor play is associated with better emotional well-being. Ferguson et al. (2025) found that more frequent outdoor play was associated with better social-emotional competence. In contrast, other findings differed according to the outcome, timing and context being examined. Poulos et al. (2026) found higher positive affect after outdoor and gymnasium recess than after classroom recess, but no significant differences in negative affect between settings. Lee et al. (2025) also found different associations according to the timing of outdoor play. Dodd et al. (2026) provides longer-term evidence. More frequent outdoor play during the preschool years was associated with a greater likelihood of following a low and stable trajectory of internalising and externalising symptoms through childhood. However, the studies differ in children's ages, research designs, measures of outdoor play and emotional outcomes. Therefore, the evidence should not be interpreted as showing one consistent effect across all children or forms of emotional well-being. === '''Consistency of recent research findings''' === Recent findings are not consistent across all emotional and developmental outcomes. Ferguson et al. (2025) found that more frequent outdoor play was associated with better social-emotional competence and greater [[Prosocial Behaviour|prosocial behaviour]]. In contrast, Davenport et al. (2024) found that most associations between outdoor play and the physical, [[Cognitive psychology|cognitive]] and social-emotional developmental indicators examined were not statistically significant. This differences shows that positive association with outdoor play are not found across all developmental outcomes. Findings can also differ according to the emotional outcome being measured. Poulos et al. (2026) found higher positive affect after outdoor and gymnasium recess than after classroom recess, but no significant differences in negative affect between the three recess settings. Lee et al. (2025) found that more afternoon outdoor play was associated with lower emotional dysregulation, while more outdoor play earlier and later in the day was associated with higher emotional dysregulation. These findings suggest that the association can differ according to both the emotional outcome and the timing of outdoor play. The time period being examined also differs between studies. Dodd et al. (2026) found that more frequent outdoor play during the preschool years was associated with lower odds of belonging to less favourable internalising and externalising symptom trajectory across childhood. This is different from the studies done by Poulos et al. (2026), which examined children's emotional states immediately after the recess. Therefore, recent research includes both immediate emotional outcomes and longer-term patterns of emotional functioning. Associations may vary across children and play contexts. Ferguson et al. (2025) reported differences according to ethnicity and whether outdoor play occurred on school days or weekends. Together, these findings suggest that the association between outdoor play and emotional well-being are not same across outcomes.The studies differ in children's age, research designs, measures of outdoor play, and emotional outcomes. Thus, findings should not be treated as evidence of one single effect. === '''Strengths and limitations of current research''' === The strength of the evidence also differs according to research design. Dodd et al. (2026) used longitudinal data from r4,151 children and measured outdoor play during the preschool years approximately 2 to 4 years old, and internalising and externalising symptoms trajectories were measured later through to age 8. This strengthens the evidence about temporal ordering because outdoor play was measured before the later emotional outcomes. However, longitudinal evidence does not establish cause and effect, and the study relied on parent-reported measures. Causal interpretation is also limited in other studies. Lee et al. (2025) used observational data and considered the possibility of reverse causation when interpreting associations between the timing of outdoor play and emotional dysregulation. This means the findings cannot establish whether outdoor play influenced emotional dysregulation or whether children's emotional functioning influenced when they played outdoors. Measurement of outdoor play is another important consideration. Davenport et al. (2024) used both parent-reported and device-measured outdoor play and examined whether associations were independent of outdoor moderate-to-vigorous physical activity (MVPA). This is important because outdoor play and outdoor physical activity are related but should not be treated as interchangeable measures. However, the sample was relatively small and most tested associations with developmental outcomes were not statistically significant. Limitations are also present across the wider outdoor-play literature. De Lannoy et al. (2023) identified 275 Canadian outdoor-play publications and found that cross-sectional designs were the most common. Mental and emotional development had also received less research attention than physical health and development. This suggests that the evidence base for emotional well-being remains less developed than some other areas of outdoor-play research. T'''able 3. ''Comparison of recent research''''' {| class="wikitable" |+ !Study !Research method !Research strength !Limitation |- | <small>Lee et al. (2025)</small> |Observational; 6 month follow-up |Examined the timing of outdoor play and tested working memory as a statistical mediator of the association with emotional dysregulation. |Observational mediation cannot establish causation; reverse causation when interpreting timing-related findings. |- |Ferguson et al. (2025) |Cross sectional; multi ethnic urban cohort (N=2,568) |Large sample allowed associations to be examined across population groups and school-day/weekend outdoor play. |Cross-sectional design cannot establish temporal direction; associations also differed across some groups and play contexts. |- |Davenport et al. (2024) |Observational; preschool sample (N=107) |Used both parent-reported and device-measured outdoor play and distinguished outdoor play from outdoor moderate-to-vigorous physical activity (MVPA) |Small sample and most tested associations with developmental outcomes were not statistically significant. |- |Dodd et al. (2026) |Longitudinal cohort (N = 4,151) |Outdoor play was measured in the preschool years before later internalising and externalising symptom trajectories. |Relied on parent reported measures, and the observational data cannot not establish conclusions. |- |Poulos et al. (2026) |Recess comparison study (N=317) |Compared positive and negative affect after outdoor gymnasium and classroom recess |Examined immediate affect during an extreme-heat context; higher positive affect was also found after gymnasium recess, so the result was not specific to outdoor recess. |} As shown in table 3, the recent evidence has different methodological strengths and limitations. Longitudinal design provide stronger evidence about temporal ordering than cross-sectional design studies, while device based measured can address some limitations of parent report. However, much of the evidence remains observational, differences in emotional outcomes, measures of outdoor play and play contexts limit the direct comparison between studies. Future research could benefit from more consistent measures of outdoor play, stronger longitudinal and experimental designs and greater attention to emotional outcomes across different children and play contexts. {| class="wikitable" | valign="top" |{{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {Why should the recent findings not be interpreted as showing single consistent effect of outdoor play on children's emotional well-being? |type="()"} -A. Because all the studies used different countries. +B. Because studies differed in emotional outcomes, measures of outdoor play, timing, context and research design. -C. Because longitudinal studies are always more reliable and accurate. -D. Because outdoor play only affects positive outcomes. </quiz> {{Robelbox/close}} |} == '''How do families, communities and schools support outdoor play opportunities?''' == [[File:Coalition Builds New Playground in One Day for Chicora-Cherokee Community (11054532905).jpg|thumb|325x325px|figure 5]] Outdoor play opportunities are shaped by children's social and physical environments. Beekhuizen et al. (2025) identified parents, outdoor play environments, communities and time constraints as environmental factors in inclusive outdoor play. The study also identified autonomy, growing up together, making contact and adapting ways of playing as factors that affected participation. The 2025 Position Statement on Active Outdoor Play recommends increasing opportunities for active outdoor play where people live, learn, work and play (Lee et al., 2025). It also recommends collaboration across sectors and settings to support equitable access. This provides a broader context for considering the roles of families, communities and schools. === '''Families''' === Parents can influence whether children have opportunities to play outdoors. Beekhuizen et al. (2025) identified as an environmental factor in inclusive outdoor play. Children with disabilities described parents as important in encouraging participation. For some children, parents also helped to explain their disability to other children (Beekhuizen et al., 2025).   Broader research also identifies parental factors in children's outdoor play. A systematically reviewed 21 peer reviewed studies of children aged 0 to 12 years found that the importance placed on outdoor play was associated with how much time children spent playing outdoors (Boxberger and Reimers, 2019). Evidence for parental encouragement and support was less consistent across children (Boxberger and Reimers, 2019). This suggests that family influence is not limited to direct encouragement. Parents attitude towards outdoor play may shape children's opportunities to play outdoor. However, the review identified some associations but does not show that parental attitude caused greater outdoor play. Parental support also requires to allow for children for children's independence during outdoor play. Support can make participation possible, but it does not always require direct parental involvement (Beekhuizen et al., 2025). This is particularly relevant when children want more control over how and where they play. Research on independent mobility also shows that children and parents may differ how much independence they prefer (Han et al., 2022). The study identified different patterns in children and parents preferences for independent mobility. These findings show that parental support and autonomy do not always involve the same level of parental involvement. Some children may need support to access or join outdoor play while also wanting for greater independence. Beekhuizen et al. (2025) also recommended providing children and parents knowledge about disabilities and possible adaptations that could support participation. Time constraints can also limit family-level opportunities for outdoor play. Beekhuizen et al. (2025) reported that some children had less time to play outdoors because of parents' work schedules, after-school arrangements and longer travel between home and school. This means that opportunities for outdoor play can be restricted even when children want to play and parents are supportive. === '''Communities''' === Community conditions can affect whether children have safe and inclusive opportunities for outdoor play. Beekhuizen et al. (2025) described physical and social safety as important for inclusive outdoor play. Some playground structures also made participation difficult for children with disabilities. A systematic review of 25 studies found that both physical and social neighbourhood factors were associated with children's outdoor play (Visser & van Aalst, 2022). Social factors included perceived safety, social cohesion and the presence of other children. However, the studies did not identify one neighbourhood feature that consistently explained children's outdoor play across all settings. The social environment may also affect whether children can join others. Children with disabilities described smaller communities, including villages and schools, as places where children and parents could become more familiar with disability. Greater familiarity was associated with greater acceptance and stronger connections with other children (Beekhuizen et al., 2025). Observational research provides more evidence about what happens when children play together. Beekhuizen et al. (2026) observed 63 children with and without disabilities during six inclusive outdoor-play sessions and found children with disabilities had lower playfulness scores than children without disabilities. Unfamiliarity could also restrict social inclusion because children preferred to play with peers they already knew. This means providing the same outdoor space does not necessarily provide the same opportunity to participate. The 2025 Position Statement on Active Outdoor Play recommends collaboration across sectors and settings to support equitable access to active outdoor play (Lee et al., 2025). The findings reviewed to show why both physical and social conditions matter. Children need places that can be accessed, but familiarity, safety and opportunities to join others can also affect participation. However, the evidence does not show that one community feature alone will increase outdoor play or improve emotional well-being. === '''Schools''' === Schools can provide opportunities for children with and without disabilities to become more familiar with one another. Beekhuizen et al. (2025) identified growing up together and making contact as interacting factors in inclusive outdoor play. Children described familiarity with other children as making contact easier. School circumstances can also affect the time available for outdoor play. Some children attending special primary education described long travel times between school and home as reducing their opportunities to play outdoors. Beekhuizen et al. (2025) identified these experiences as part of time constraints. The physical school environment can also be changed to support outdoor activity and socio-emotional outcomes. Bikomeye et al. (2021) systematically reviewed six experimental studies of schoolyard greening. The interventions involved adding greenery and natural elements to schoolyards. Across the included studies, the review reported generally positive findings for physical activity and socioemotional health. However, the review included only six studies. Schoolyard greening is also a specific intervention and should not be treated as evidence that all forms of outdoor play improve children's emotional well-being. Recess provides another school setting in which children's emotional experiences have been examined directly. Poulos et al. (2026) studied 317 Year 4 and 5 children during extreme heat. Positive affect was higher after outdoor and gymnasium recess than after classroom recess. There were no significant differences in negative affect between the three settings. Poulos et al. (2026) also identified implications for school health, policy and equity. The study discussed heat-adaptive infrastructure as one way to support access to recess environments during extreme heat. However, the findings do not show that outdoor recess is always better than indoor recess because positive affect was also higher after gymnasium recess. * Schools can provide opportunities for children with and without disabilities to become familiar with one another. Beekhuizen et al. (2025) identified growing up together and making contact as interacting factors in inclusive outdoor play. Children described familiarity with other children as making contact easier. * School circumstances can also affect the time and opportunities available for outdoor play. Some children attending special primary education described long travel times between school and home as reducing the time available to play outdoors. Beekhuizen et al. (2025) identified these experiences under time constraints. * Recess provides another school setting in which children's emotional experiences have been examined. Poulos et al. (2026) studied 317 year 4 and 5 children during extreme heat weather and found significantly higher positive affect after outdoor and gymnasium recess than after classroom recess. There were no significant differences in negative affect between the three recess settings. * Poulos et al. (2026) identified implications for school health, policy and equity, including the need for heat adaptive infrastructure to support access to recess environments during extreme heat. However, the findings do not show that outdoor recess is always better than indoor recess because positive affect was also higher following gymnasium recess. {{Robelbox|theme=12|title=Quiz}} <quiz display=simple> {Children who have access to the same outdoor playground may still have different opportunities to participate in play. |type="()"} + True - False </quiz> {{Robelbox/close}} {{Robelbox|theme=12|title=Quiz}} <quiz display=simple> {Outdoor play has the same relationship with children's emotional well-being regardless of how door play or emotional well being is measured. |type="()"} - True + False </quiz> {{Robelbox/close}} {| class="wikitable" |Scenario Two primary school aged children A and B enjoy playing outdoors. They both lived near the same playground. Child A was very familiar with the playground and knows several other children who play there and easily join the games. While child B has disability, uses mobility device and does not know other children at playground. Some parts of the playground are difficult to access and joining other children who are already playing can also be challenging. Child B's parents can provide support, although the child also prefers to play more independently. Consider both children can access the same playground, but do they have same level opportunities to take part in outdoor play? |} == '''Conclusion''' == * Outdoor play and children's emotional well-being are measured in different ways across recent research. Outdoor play is not equivalent to outdoor physical activity, while emotional outcomes include emotional dysregulation, social-emotional competence, positive and negative affect, and internalising and externalising symptoms. These differences need to be considered when findings across studies are compared. * Research also provides mixed evidence about how outdoor play may be related to emotional well-being. Gross's (2015) emotion-regulation framework can be applied to emotional situations experienced during play, but it does not show that outdoor play improves emotion regulation. Lee et al. (2025) provides more direct evidence of a possible cognitive process, with working memory statistically mediating the association between afternoon outdoor play and lower emotional dysregulation. However, this observational finding does not establish causation. * Recent findings are not consistent across all outcomes or contexts. Ferguson et al. (2025) reported associations with better social-emotional competence, Dodd et al. (2026) found longitudinal associations with internalising and externalising symptom trajectories, and Poulos et al. (2026) found differences in positive but not negative affect following recess. In contrast, most associations examined by Davenport et al. (2024) were not statistically significant. * Recent findings are not consistent across all outcomes or contexts. Ferguson et al. (2025) reported associations with better social-emotional competence, Dodd et al. (2026) found longitudinal associations with internalising and externalising symptom trajectories, and Poulos et al. (2026) found differences in positive but not negative affect following recess. In contrast, most associations examined by Davenport et al. (2024) were not statistically significant. * Overall, current research supports an association between outdoor play and some aspects of children's emotional well-being but does not establish one consistent effect. Differences in measurement, research design, children and play contexts remain important when interpreting the evidence. ==See also== {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} https://www-taylorfrancis-com.ezproxy.canberra.edu.au/books/mono/10.4324/9781003349655/right-child-play-naomi-lott Book Chapter, 2 {{ic|Move to References and cite}} https://en.wikipedia.org/wiki/Emotional_dysregulation<nowiki/>- Wikipedia article {{ic|Use an internal links as shown in Tutorial 2}} https://en.wikipedia.org/wiki/Autonomy<nowiki/>- Wikipedia article {{ic|Use an internal links as shown in Tutorial 2}} https://en.wikipedia.org/wiki/Longitudinal_study<nowiki/>-Wikipedia article {{ic|Use an internal links as shown in Tutorial 2}} [[Cognitive psychology|https://en.wikiversity.org/wiki/Cognitive_psychology]]-Wikipedia article https://en.wikipedia.org/wiki/Affordance<nowiki/>-Wikipedia article {{ic|Use an internal links as shown in Tutorial 2}} ==References== {{Hanging indent|1= Beekhuizen, R. Q., Bolster, E. A. M., Gorter, J. W., Henry, N. L., Visser, K., Wittink, H., Kotte, E. M. W., Sol, M. E., & Bloemen, M. A. T. (2025). Play Together? Unveiling Facilitators and Barriers to Inclusive Outdoor Play for Dutch Children With and Without Disabilities: A Qualitative Study. Child: Care, Health & Development, 51(6), Article e70154. https://doi.org/10.1111/cch.70154 Biino, V., Pesce, C., & Martins, C. (2025). Motor Skill Development at Preschool Age in Girls and Boys: The Role of Outdoor Free Play. Children, 12(5), Article 594. https://doi.org/10.3390/children12050594 Davenport, C., Kuzik, N., Larouche, R., & Carson, V. (2025). The Associations Between Parental-Reported and Device-Based Measured Outdoor Play and Health Indicators of Physical, Cognitive, and Social–Emotional Development in Preschool-Aged Children. Pediatric Exercise Science, 37(2), 102–111. https://doi.org/10.1123/pes.2023-0119 de Lannoy, L., Barbeau, K., Seguin, N., & Tremblay, M. S. (2023). Scoping review of children’s and youth’s outdoor play publications in Canada. Chronic Diseases in Canada, 43(1), 1–13. https://doi.org/10.24095/hpcdp.43.1.01 Dodd, H. F., Cordwell, K., Hesketh, K., Johnstone, A., de la Torre-Luque, A., & McCrorie, P. (2026). Early outdoor play predicts trajectories of child mental health in a population-based cohort. Journal of Child Psychology and Psychiatry. https://doi.org/10.1111/jcpp.70175 Ferguson, M., Teyhan, A., Lovell, R., Dodd, H., Wheeler, B., & McEachan, R. (2025). The association between park visits, outdoor play and child social-emotional competency in a multi-ethnic, urban cohort. Wellbeing, Space and Society, 9, Article 100293. https://doi.org/10.1016/j.wss.2025.100293 Gross, J. J. (2015). Emotion Regulation: Current Status and Future Prospects. Psychological Inquiry, 26(1), 1–26. https://doi.org/10.1080/1047840X.2014.940781 Lee, E.-Y., de Lannoy, L., Kim, Y.-B., Rathod, A., James, M. E., Lopes, O., Nasrallah, B., Thankarajah, A., Adjei-Boadi, D., de Barros, M. I. A., Duncan, S., Miller, R. M., Mygind, L., Vanderloo, L. M., Wang, P.-Y., & Tremblay, M. S. (2025). 2025 Position statement on active outdoor play. The International Journal of Behavioral Nutrition and Physical Activity, 22(1), Article 117. https://doi.org/10.1186/s12966-025-01813-9 Lee, J. J., Flouri, E., & Jackson, Y. (2025). The Role of Timing and Amount of Outdoor Play in Emotional Dysregulation in Preschool Children. Child: Care, Health & Development, 51(1), Article e70020. https://doi.org/10.1111/cch.70020 Morgenthaler, T., Lynch, H., Loebach, J., Pentland, D., & Schulze, C. (2024). Using the Theory of Affordances to Understand Environment–Play Transactions: Environmental Taxonomy of Outdoor Play Space Features—A Scoping Review. The American Journal of Occupational Therapy, 78(4), Article 7804185120. https://doi.org/10.5014/ajot.2024.050606 Pereira, J. V., Vila-Nova, F., Veiga, G., Lopes, F., & Cordovil, R. (2024). Associations between outdoor play features and children’s behavior and health: A systematic review. Health & Place, 87, Article 103235. https://doi.org/10.1016/j.healthplace.2024.103235 Poulos, A., Hassan, U. A., Wilson, K., Price, P. M., Vanos, J., & Quilla, J. (2026). Differences in Schoolchildren’s Emotional State After Indoor Versus Outdoor Recess in Extreme‐Heat Weather. The Journal of School Health, 96(4), Article e70135. https://doi.org/10.1111/josh.70135 }} ==External links== {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} https://www.child-encyclopedia.com/outdoor-play<nowiki/>-Encyclopedia in early childhood development https://www.outdoorplaycanada.ca/wp-content/uploads/2026/03/The-2025-AOP10-Position-Statement.pdf<nowiki/>-Position Statement https://www.who.int/news/item/24-04-2019-to-grow-up-healthy-children-need-to-sit-less-and-play-more<nowiki/>-World Health Organisation [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Children]] [[Category:Motivation and emotion/Book/Nature]] [[Category:Motivation and emotion/Book/Well-being]] 3tvt1bjvo858dp109hv5xm4kxz690hy 2835499 2835492 2026-10-02T11:56:44Z Mymunu 3106327 /* Emotion regulation */ 2835499 wikitext text/x-wiki {{title|Outdoor play and children's emotional well-being:<br>How does outdoor play influence children's emotional well-being?}} __TOC__ == Overview == {| class="wikitable" |'''Case study: Part 1'''[[File:School children happily playing in playground.jpg|thumb|'''Figure 1'''. Children engaged in outdoor play, where social interactions, choice and control on the situation can create different emotional experiences.]]Imagine that... A child arrives at playground and joins a group of children who are already playing. The children are making their own game and deciding the rules as they play. At first, the child enjoys choosing where and what to play. During the game, another child changes the rules of the game and argument breaks out. The child becomes frustrated and walks away from the activity. After watching for a short time, the child returns, suggests a new idea to continue the game and re-joins the group. How might experiences like this during outdoor play influence children's emotional well-being? Emotional regulation provides one psychological framework for understanding how children may respond to situations like this during play (see figure 1). |} Outdoor play can involve more than physical movement. It can occur across playgrounds, gardens, streets and natural spaces. Outdoor play includes exploration, social interaction, choice, challenge, and engagement with the surrounding environment (Dodd et al., 2026; Pereira et al., 2024). As shown in the case study part 1, outdoor play can involve emotional situations such as [[Aggression|frustration]], disagreement, uncertainty or excitement. Gross's (2015) [[emotional regulation]] provides a [[psychological]] explanation for how children may recognise and respond to these emotional situations. Outdoor play experiences are also shaped by the environment where play takes place. Different physical and social environments can provide different opportunities for play, which means the same outdoor space may not provide the same opportunities for every child (Morgenthaler et al., 2024).This chapter examines how [[Emotional regulation|emotional,]] [[Cognitive psychology|cognitive]], social and environmental processes may help explain the relationship between outdoor play and children's [https://w.wiki/AHG6 emotional well-being.] {| class="wikitable" | ;[[File:Bulb Idea Flat Icon GIF Animation.gif|alt=Focus questions|left|99x99px|thumb]] '''Focus questions''' * '''What are outdoor play and children's emotional well-being?''' * '''How does outdoor play influence children's emotional well-being?''' * '''How do social and environmental conditions shape children's outdoor play experiences?''' * '''What does recent research show about outdoor play and children's emotional well-being?''' * '''How can families, communities and schools support outdoor play opportunities that may benefit children's emotional well-being?''' |} == '''Understanding outdoor play and children's emotional well-being''' == [[File:Water-outdoor-people-girl-play-boy-938233.jpg|thumb|'''Figure 2'''. ''Outdoor play can provide opportunities to explore, make choices, interact with others and respond to changing situations through activities such as water play.''|214x214px]] Outdoor play and children's emotional well-being are not measured as single and consistent concepts across recent research. Outdoor play may be examined as voluntary and intrinsically motivated activity, self directed play, parent reported outdoor play, or device-measured outdoor play (Binno et al., 2025; Davenport et al., 2025; Dodd et al., 2026). It should also be distinguished from outdoor moderate-to-vigorous physical activity (MVPA) because these measures do not represent the same behaviour (Davenport et al., 2025). Children's emotional well-being is also examined through different outcomes, which include [https://w.wiki/7YC8 emotional dysregulation], social-emotional competence, positive and negative affect, and internalising or externalising symptoms (Dodd et al., 2026; Ferguson et al., 2025; Lee et al., 2025; Poulos et al., 2026). These differences need to be considered when findings across the studies are compared. === Outdoor play === Outdoor play is voluntary and and intrinsically motivated activity that occurs in outdoor environments such as gardens, playgrounds, parks and natural spaces (Dodd et al., 2026). Free play can be also self-directed, allowing children to interact freely with the environment and have [https://w.wiki/4NyU autonomy] to make choices about their activities (Biino et al., 2025). Outdoor play should not be treated as the same as outdoor physical activity. The recent research outdoor play and outdoor moderate- to-vigorous physical activity (MVPA) were examined as separate measures (Davenport et al., 2025). This distinction is important because outdoor play intensity of physical activity do not represent the same behaviour. === Children's emotional well-being === Children's emotional well-being is not represented by a single common outcome across recent outdoor play research. Emotional dysregulation has been examined in relation to the amount and timing of outdoor play (Lee et al., 2025), while social-emotional competence includes social emotional difficulties and [[Prosocial behavior/Keywords/Definitions|prosocial behaviour]] (Ferguson et al., 2025). Other studies have examined positive and negative affect following recess (Poulos et al., 2026) and trajectories of internalising and externalising symptoms across childhood (Dodd et al., 2026). These outcomes represent different aspects and timeframes of emotional functioning, so they should not be treated as equivalent when findings are compared. '''Table 1''' ''Emotional outcomes examined in recent research on outdoor play and children's emotional well-being'' {| class="wikitable" |+ !Study !Outcome examined !What the outcome represents |- |Lee et al. (2025) |Emotional dysregulation |Difficulties in emotional regulation; examined in relation to the amount of timing of outdoor play |- |Ferguson et al. (2025) |Social-emotional competence |Social-emotional difficulties and prosocial behaviour |- |Poulos et al. (2026) |Positive and negative affect |Children's affect following recess across different settings |- |Dodd et al. (2026) |Internalising and externalising symptoms |Internalising: emotional symptoms and peer problems Externalising: conduct problems and hyperactivity- inattention |} Note. Outcome descriptions are based on the measures and constructs reported in the above cited studies. See Table 1. As shown in Table 1, the studies do not measure the same aspect or time frame of children's emotional functioning. Affect immediately following recess should not be treated as equivalent to emotional dysregulation measured over time or trajectories of internalising and externalising symptoms across childhood. This difference need to be considered when findings across studies are compared. '''Case study: part 2''' ''What is being measured?'' {| class="wikitable" | valign="top" |[[File:Children marbles.jpg|thumb|221x221px|'''Figure 3'''. ''Children's immediate emotional responses during outdoor play is different from long-term emotional functioning.'']]The child in the Case study: Part 1 becomes frustrated when the rules of the game change. This immediate emotional response is different from a longer-term pattern of emotional dysregulation or internalising symptoms. Research on outdoor play measures these outcomes across different time frames and contexts. When findings are compared, it is important to consider which aspect of emotional well-being is measured. {{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {A child's positive or negative affect immediately after recess represents the same emotional outcome as longer-term internalising or externalising symptoms. |type="()"} - True + False </quiz> {{Robelbox/close}} |} == '''How does outdoor play influence children's emotional well-being?''' == Outdoor play may be related to children's emotional well-being through emotional, cognitive, and social processes (Dodd et al., 2026). Possible pathways discussed in the recent research include cognitive, social and emotional skills, social interaction, physical activity, connection with the nature and adventurous play (Dodd et al., 2026). However, these pathways have not all been directly tested as mechanisms, and many of the outdoor play research remain observational (Dodd et al., 2026; de Lannoy et al., 2023). Psychological theory can help to explain how and why outdoor play experiences may influence children's emotional well-being. Although the evidence does not yet show that psychological processes cause the relationship between outdoor play and children's emotional well-being. Emotion involves more than subjective feelings. Scherer (2005) described emotion as coordinated changes across cognitive appraisal, physiological responses, action tendencies, expression and subjective feelings. Therefore, physiological responses are one component of an emotional response rather than a separate explanation for the effects of outdoor play. Scherer (2005) did not examine outdoor play, so this framework does not provide evidence that outdoor play changes children's physiological responses or emotional well-being. === '''Emotion regulation''' === Emotion regulation provides a psychological framework for understanding how children may manage emotional situations during outdoor play. Gross (2015) described emotion regulation as a process involving identification, selection and implementation. Identification concerns deciding whether to regulate an emotion, selection concerns selecting regulation strategy and implementation concerns applying chosen response into practice. Gross (2015) also described situation selection, situation modification, attentional deployment cognitive change and response modulation. During outdoor play, children may experience frustration, conflict, disagreement, uncertainty or changes to their activity. Gross's framework can be applied to these situations to consider how the children recognise an emotional response, choose strategies to manage and act on chosen strategies. However, Gross (2015) did not examine outdoor play, so applying the framework does not show that outdoor play improves children's emotion regulation. Broader research on children's play has also examined emotional functioning. Veraksa et al. (2025) systematically reviewed 33 studies on non-therapeutic play among children aged 3 to 7 and identified evidence involving emotional regulation, emotional intelligence, and negative emotional symptoms. The review included outdoor play alongside several other forms of play, so its findings should not be interpreted as evidence that outdoor play alone improves emotion regulation. {| class="wikitable" | valign="top" |'''Case study: Part 3'''[[File:14Y Ncdc july 5th-802.jpg|thumb|202x202px|'''Figure 4'''. ''Children can respond differently to emotional situations that occur during outdoor play.'']]When the rules of game change, the child becomes frustrated and decides to step away. After a short time the child returns and suggests a different way to continue the game (see Figure 4). Suggesting a change to the game can be considered an example of situation modification. This shows how Gross's emotion regulation framework can be applied to an emotional situation during outdoor play. {{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {What does Gross (2015) emotion regulation framework show when it is applied to the outdoor-play scenario?. |type="()"} -A. Outdoor play causes better emotion regulation. +B. Situation modification can help explain how the child responds to the situation. -C. Children regulate emotions better outdoors than indoors. -D. Stepping away from play always improves emotional well-being. </quiz> {{Robelbox/close}} |} === '''Working memory and cognitive process''' === Working memory can be one cognitive process involved in the association between outdoor play and emotional dysregulation. Lee et al. (2025) examined 325 preschool children and tested working memory as a statistical mediator. Outdoor play was examined across three periods of the day; wake up to noon, noon to 6 pm, and 6 pm to bedtime. The findings differed according to the timing of outdoor play. More outdoor play between noon and 6 pm was associated with lower emotional dysregulation. In contrast, more outdoor play before noon and after 6 pm was associated with higher emotional dysregulation. Afternoon outdoor play was also associated with better working memory, and better working memory was associated with lower emotional dysregulation. When working memory was included in the analysis, the association between afternoon outdoor play and emotional dysregulation was no longer statistically significant. Lee et al. (2025) reported this as full mediation. This suggests that working memory may be involved in the association between afternoon outdoor play and lower emotional dysregulation. However, the study was observational, so the mediation analysis does not show that outdoor play caused better working memory or lower emotional dysregulation. Johnstone et al. (2022) reviewed 36 studies of nature-based [[early childhood education]]. The review found very low certainty evidence for some social, emotional, and cognitive outcomes, including [[self-regulation]], while findings for attention were inconsistent. Although, the review examined nature-based early childhood education rather than outdoor play. Therefore, it does not show that working memory explains the association between outdoor play and children's [https://w.wiki/AHG6 emotional well-being]. == '''How do social and environmental conditions influence on children's outdoor play experiences?''' == Outdoor play opportunities depend on social and physical environments. Children may have access to same outdoor space but may not have same opportunities for play. Beekhuizen et al. (2025) identified personal, interacting and environmental factors that could support or restrict inclusive outdoor play. These difference can be considered through [https://w.wiki/VYfL affordance theory], which examines the opportunities for action through the relationship between an individual and the environment (Gibson, 1979). === Affordance theory and outdoor play environments === [https://w.wiki/VYfL Affordance theory] was developed by Gibson (1979) to explain the opportunities for action that an environment provides in relation to the person using it. In outdoor play, the opportunities provided by a space can depend on its physical features and how a child is able to use those features. Morgenthaler et al. (2024) applied affordance theory to children's outdoor play and examined outdoor play transactions through environmental taxonomy of outdoor play space features. Their review identified 14 categories of spaces and 284 play opportunities linked to different environmental features. Morgenthaler et al. (2024) showed that different spaces and objects can afford different forms of play, which means two children using the same outdoor play space may not experience the same play opportunities. Therefore, the theory provides a way of understanding differences between children and their use of an outdoor environment. However this study examined the opportunities for play rather than children's well-being. Pereira et al. (2024) also examined features of outdoor play spaces in a systematic review of 51 articles representing 45 primary studies. The review examined features such as fixed structures, natural elements, floor markings, loose equipment and available play areas. Some positive effects were reported, but there was substantial heterogeneity between studies. The studies differed in the environmental features examined, outcomes measures, and study methods, which made difficult to draw a clear conclusions about the effect of individual play space features (Pereira et al., 2024).Therefore, the review does not show that one particular environmental feature improves children's [https://w.wiki/AHG6 emotional well-being]. '''Table 2'''. ''Examples of environmental features and possible affordances'' {| class="wikitable" |+ !Environmental feature !Possible affordance for play |- |Fixed structures (e.g. climbing frame) |Can provide opportunity in different forms of physical activity. For example, climbing, physical play, risk-taking |- |Natural elements (e.g. tree, rocks, sand) |Environmental features can provide opportunities for exploratory play, imaginative play, sensory experiences |- |Floor markings (e.g. painted games) |Can support structured activities like rule based play, footy, tennis, etc. |- |Loose equipment (e.g. balls, tyre, boxes) |Movable environmental features that can be used during constructive play, imaginative play, creative problem solving play |- |Open play area |Running, group play, or flexible use |} Note. This table is an original synthesis based on environmental features described by Pereira et al. (2024) and affordance framework applied by Morgenthaler et al. (2024). Environmental features can afford more than one type of play and the opportunities may vary between children. {| class="wikitable" | valign="top" |'''Case study: Part 4 Same space, different opportunities''' Kim and Leo are both at the same school playground during recess. The playground has a climbing structure, a sand pit area and open natural space. * Kim quickly joins a group of children using a climbing frame. The climbing frame structure provides opportunities for physical play and social interactions. * Leo uses a sand pit with other child. He plays with loose materials and creates a sand castle and other different structures. The environment gives him an opportunity for imaginative play and social play. These examples show how the same outdoor space can afford different forms of play for different children, depending on their interests, skills and social context. {{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {Which statement best applies affordance theory to the example?. |type="()"} -A. The playground causes children to be more physically active. +B. The same playground can provide different opportunities for play depending on the child and how they use the environment. -C. Climbing structures always lead to better emotional well-being. -D. Open spaces are only useful for social play. </quiz> {{Robelbox/close}} |} === '''Social relationship and inclusion''' === Social relationships can shape whether children are able to join and continue outdoor play (Beekhuizen et al., 2025). Beekhuizen et al. (2025) identified making contact and growing up together as interacting factors in inclusive outdoor play. Familiarity with other children could make it easier to approach, communicate and play together, while joining unfamiliar children or existing game could be difficult. Affective social competence (ASC) provides a psychological framework for understanding these social interactions (Gal-Szabo et al., 2018). Gal-Szabo et al. (2018) described emotional competence as involving experiencing, sending and receiving affect, together with awareness, identification, responding with the social context and regulation. These process may be relevant when a child tries to enter a peer group, recognise other children's emotions and manage their own response during play (Gal-Szabo et al., 2018). Gal-Szabo et al. (2018) also found that situational understanding of the emotions was related to uninvolved behaviour and was marginally related to more social play. However, that the study examined preschool free play rather than specific outdoor play. Beekhuizen et al. (2025) also found that children with disabilities experienced more barriers related to making contact, adapting play and physical play environment. These findings suggest that participation in outdoor play depends on both social interaction and children's ability to respond within the play situation, but they do not establish that social play causes better emotional well-being (Beekhuizen et al., 2025; Gal-Szabo et al., 2018). === '''Autonomy, parents and time''' === Autonomy can shape how children experience outdoor play (Beekhuizen et al., 2025). Beekhuizen et al. (2025) identified autonomy as a personal factor in inclusive outdoor play. Some children valued having independence over what they do and who they play with. Some children with disabilities wanted opportunities to play outside independently without direct parental involvement. Autonomy during play may also have an emotional function. Veraksa et al. (2025), in a systematic review of non-therapeutic play, identified autonomy as one feature through which play may support emotional regulation and coping. However, the review examined several forms of play and does not show that autonomy during outdoor play specially improves children's emotional well-being. Parental support can also make outdoor play possible. Beekhuizen et al. (2025) found that parental involvement could support children's participation when a child needed help to access or participate in outdoor play. Time constraints also affected opportunities for outdoor play. Some children had less time to play outdoors because of parents' work schedule, after school arrangements or longer travel distance between home and school (Beekhuizen et al., 2025). These constraints could limit opportunities for outdoor play even when children wanted greater independence. === '''Outdoor environments and accessibility''' === Outdoor play environment can support or restrict children's participation (Beekhuizen et al., 2025). Their identified both physical and social features of outdoor environments as relevant to inclusive play. Children discussed safety, including traffic near playgrounds and disputes with other children. Accessibility was particularly important for children with disabilities because opportunities for inclusive outdoor play could be affected by play environments and physical abilities. Pereira et al. (2024) also showed that heterogeneity between studies limited clear conclusion about the effects of individual outdoor play space features.. Gibson et al. (2017) reported a similar limitation for loose-parts play. Their systematic review found insufficient quantitative evidence to determine whether loose-parts interventions affected children's cognitive, social or emotional development. Together, these findings show that features of outdoor environments can support or restrict opportunities for play. However, current evidence does not establish a particular environmental feature that improves children's emotional well-being ( Beekhuizen et al., 2025; Gibson et al., 2017; Pereira et al., 2024). {| class="wikitable" | valign="top" |'''Case study: Part 5 Same play space, different experiences''' {| class="wikitable" |Kim and Leo uses the same school playground. Kim already knows many children and easily joins the group activity. Leo uses a mobility device and finds some areas of playground is difficult to access. Leo also does not know many children who are already playing. Leo also prefers to play independently when possible. |} The two children have access to the same playground space, but their opportunities to participate is different. Affordance theory can help to understand how the physical environment provides opportunities depending on child and how the space can be used. Beekhuizen et al. (2025) also identified making contact, familiarity, autonomy and accessibility as factors that could support or restrict inclusive outdoor play. Physical accessibility may affect whether a child can use part of playground, while familiarity with other children may affect whether the child can enter social play. Parental support may also help participation in some situations, while the child may still value greater independence {{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {Why might two children have different outdoor play experiences even they use the same playground?. |type="()"} +A. Physical, social and personal contributions can affect who child are able to participate. -B. Outdoor spaces provide the same opportunities for every child. -C. Accessibility is the only factor that affects outdoor play.. -D. Children who know other children always have better emotional well-being. </quiz> {{Robelbox/close}} |} == '''What does recent research show about outdoor play and children's emotional well-being?''' == Recent research does not claim a consistent association between outdoor play and children's emotional well-being. The findings are mixed across different emotional outcomes being measured, the timing of outdoor play, children's behaviours, and the methods used to measure outdoor play. These differences are significant when interpreting whether outdoor play is associated with better emotional well-being. Ferguson et al. (2025) found that more frequent outdoor play was associated with better social-emotional competence. In contrast, other findings differed according to the outcome, timing and context being examined. Poulos et al. (2026) found higher positive affect after outdoor and gymnasium recess than after classroom recess, but no significant differences in negative affect between settings. Lee et al. (2025) also found different associations according to the timing of outdoor play. Dodd et al. (2026) provides longer-term evidence. More frequent outdoor play during the preschool years was associated with a greater likelihood of following a low and stable trajectory of internalising and externalising symptoms through childhood. However, the studies differ in children's ages, research designs, measures of outdoor play and emotional outcomes. Therefore, the evidence should not be interpreted as showing one consistent effect across all children or forms of emotional well-being. === '''Consistency of recent research findings''' === Recent findings are not consistent across all emotional and developmental outcomes. Ferguson et al. (2025) found that more frequent outdoor play was associated with better social-emotional competence and greater [[Prosocial Behaviour|prosocial behaviour]]. In contrast, Davenport et al. (2024) found that most associations between outdoor play and the physical, [[Cognitive psychology|cognitive]] and social-emotional developmental indicators examined were not statistically significant. This differences shows that positive association with outdoor play are not found across all developmental outcomes. Findings can also differ according to the emotional outcome being measured. Poulos et al. (2026) found higher positive affect after outdoor and gymnasium recess than after classroom recess, but no significant differences in negative affect between the three recess settings. Lee et al. (2025) found that more afternoon outdoor play was associated with lower emotional dysregulation, while more outdoor play earlier and later in the day was associated with higher emotional dysregulation. These findings suggest that the association can differ according to both the emotional outcome and the timing of outdoor play. The time period being examined also differs between studies. Dodd et al. (2026) found that more frequent outdoor play during the preschool years was associated with lower odds of belonging to less favourable internalising and externalising symptom trajectory across childhood. This is different from the studies done by Poulos et al. (2026), which examined children's emotional states immediately after the recess. Therefore, recent research includes both immediate emotional outcomes and longer-term patterns of emotional functioning. Associations may vary across children and play contexts. Ferguson et al. (2025) reported differences according to ethnicity and whether outdoor play occurred on school days or weekends. Together, these findings suggest that the association between outdoor play and emotional well-being are not same across outcomes.The studies differ in children's age, research designs, measures of outdoor play, and emotional outcomes. Thus, findings should not be treated as evidence of one single effect. === '''Strengths and limitations of current research''' === The strength of the evidence also differs according to research design. Dodd et al. (2026) used longitudinal data from r4,151 children and measured outdoor play during the preschool years approximately 2 to 4 years old, and internalising and externalising symptoms trajectories were measured later through to age 8. This strengthens the evidence about temporal ordering because outdoor play was measured before the later emotional outcomes. However, longitudinal evidence does not establish cause and effect, and the study relied on parent-reported measures. Causal interpretation is also limited in other studies. Lee et al. (2025) used observational data and considered the possibility of reverse causation when interpreting associations between the timing of outdoor play and emotional dysregulation. This means the findings cannot establish whether outdoor play influenced emotional dysregulation or whether children's emotional functioning influenced when they played outdoors. Measurement of outdoor play is another important consideration. Davenport et al. (2024) used both parent-reported and device-measured outdoor play and examined whether associations were independent of outdoor moderate-to-vigorous physical activity (MVPA). This is important because outdoor play and outdoor physical activity are related but should not be treated as interchangeable measures. However, the sample was relatively small and most tested associations with developmental outcomes were not statistically significant. Limitations are also present across the wider outdoor-play literature. De Lannoy et al. (2023) identified 275 Canadian outdoor-play publications and found that cross-sectional designs were the most common. Mental and emotional development had also received less research attention than physical health and development. This suggests that the evidence base for emotional well-being remains less developed than some other areas of outdoor-play research. T'''able 3. ''Comparison of recent research''''' {| class="wikitable" |+ !Study !Research method !Research strength !Limitation |- | <small>Lee et al. (2025)</small> |Observational; 6 month follow-up |Examined the timing of outdoor play and tested working memory as a statistical mediator of the association with emotional dysregulation. |Observational mediation cannot establish causation; reverse causation when interpreting timing-related findings. |- |Ferguson et al. (2025) |Cross sectional; multi ethnic urban cohort (N=2,568) |Large sample allowed associations to be examined across population groups and school-day/weekend outdoor play. |Cross-sectional design cannot establish temporal direction; associations also differed across some groups and play contexts. |- |Davenport et al. (2024) |Observational; preschool sample (N=107) |Used both parent-reported and device-measured outdoor play and distinguished outdoor play from outdoor moderate-to-vigorous physical activity (MVPA) |Small sample and most tested associations with developmental outcomes were not statistically significant. |- |Dodd et al. (2026) |Longitudinal cohort (N = 4,151) |Outdoor play was measured in the preschool years before later internalising and externalising symptom trajectories. |Relied on parent reported measures, and the observational data cannot not establish conclusions. |- |Poulos et al. (2026) |Recess comparison study (N=317) |Compared positive and negative affect after outdoor gymnasium and classroom recess |Examined immediate affect during an extreme-heat context; higher positive affect was also found after gymnasium recess, so the result was not specific to outdoor recess. |} As shown in table 3, the recent evidence has different methodological strengths and limitations. Longitudinal design provide stronger evidence about temporal ordering than cross-sectional design studies, while device based measured can address some limitations of parent report. However, much of the evidence remains observational, differences in emotional outcomes, measures of outdoor play and play contexts limit the direct comparison between studies. Future research could benefit from more consistent measures of outdoor play, stronger longitudinal and experimental designs and greater attention to emotional outcomes across different children and play contexts. {| class="wikitable" | valign="top" |{{Robelbox|theme=12|title=Test your learning}} <quiz display=simple> {Why should the recent findings not be interpreted as showing single consistent effect of outdoor play on children's emotional well-being? |type="()"} -A. Because all the studies used different countries. +B. Because studies differed in emotional outcomes, measures of outdoor play, timing, context and research design. -C. Because longitudinal studies are always more reliable and accurate. -D. Because outdoor play only affects positive outcomes. </quiz> {{Robelbox/close}} |} == '''How do families, communities and schools support outdoor play opportunities?''' == [[File:Coalition Builds New Playground in One Day for Chicora-Cherokee Community (11054532905).jpg|thumb|325x325px|figure 5]] Outdoor play opportunities are shaped by children's social and physical environments. Beekhuizen et al. (2025) identified parents, outdoor play environments, communities and time constraints as environmental factors in inclusive outdoor play. The study also identified autonomy, growing up together, making contact and adapting ways of playing as factors that affected participation. The 2025 Position Statement on Active Outdoor Play recommends increasing opportunities for active outdoor play where people live, learn, work and play (Lee et al., 2025). It also recommends collaboration across sectors and settings to support equitable access. This provides a broader context for considering the roles of families, communities and schools. === '''Families''' === Parents can influence whether children have opportunities to play outdoors. Beekhuizen et al. (2025) identified as an environmental factor in inclusive outdoor play. Children with disabilities described parents as important in encouraging participation. For some children, parents also helped to explain their disability to other children (Beekhuizen et al., 2025).   Broader research also identifies parental factors in children's outdoor play. A systematically reviewed 21 peer reviewed studies of children aged 0 to 12 years found that the importance placed on outdoor play was associated with how much time children spent playing outdoors (Boxberger and Reimers, 2019). Evidence for parental encouragement and support was less consistent across children (Boxberger and Reimers, 2019). This suggests that family influence is not limited to direct encouragement. Parents attitude towards outdoor play may shape children's opportunities to play outdoor. However, the review identified some associations but does not show that parental attitude caused greater outdoor play. Parental support also requires to allow for children for children's independence during outdoor play. Support can make participation possible, but it does not always require direct parental involvement (Beekhuizen et al., 2025). This is particularly relevant when children want more control over how and where they play. Research on independent mobility also shows that children and parents may differ how much independence they prefer (Han et al., 2022). The study identified different patterns in children and parents preferences for independent mobility. These findings show that parental support and autonomy do not always involve the same level of parental involvement. Some children may need support to access or join outdoor play while also wanting for greater independence. Beekhuizen et al. (2025) also recommended providing children and parents knowledge about disabilities and possible adaptations that could support participation. Time constraints can also limit family-level opportunities for outdoor play. Beekhuizen et al. (2025) reported that some children had less time to play outdoors because of parents' work schedules, after-school arrangements and longer travel between home and school. This means that opportunities for outdoor play can be restricted even when children want to play and parents are supportive. === '''Communities''' === Community conditions can affect whether children have safe and inclusive opportunities for outdoor play. Beekhuizen et al. (2025) described physical and social safety as important for inclusive outdoor play. Some playground structures also made participation difficult for children with disabilities. A systematic review of 25 studies found that both physical and social neighbourhood factors were associated with children's outdoor play (Visser & van Aalst, 2022). Social factors included perceived safety, social cohesion and the presence of other children. However, the studies did not identify one neighbourhood feature that consistently explained children's outdoor play across all settings. The social environment may also affect whether children can join others. Children with disabilities described smaller communities, including villages and schools, as places where children and parents could become more familiar with disability. Greater familiarity was associated with greater acceptance and stronger connections with other children (Beekhuizen et al., 2025). Observational research provides more evidence about what happens when children play together. Beekhuizen et al. (2026) observed 63 children with and without disabilities during six inclusive outdoor-play sessions and found children with disabilities had lower playfulness scores than children without disabilities. Unfamiliarity could also restrict social inclusion because children preferred to play with peers they already knew. This means providing the same outdoor space does not necessarily provide the same opportunity to participate. The 2025 Position Statement on Active Outdoor Play recommends collaboration across sectors and settings to support equitable access to active outdoor play (Lee et al., 2025). The findings reviewed to show why both physical and social conditions matter. Children need places that can be accessed, but familiarity, safety and opportunities to join others can also affect participation. However, the evidence does not show that one community feature alone will increase outdoor play or improve emotional well-being. === '''Schools''' === Schools can provide opportunities for children with and without disabilities to become more familiar with one another. Beekhuizen et al. (2025) identified growing up together and making contact as interacting factors in inclusive outdoor play. Children described familiarity with other children as making contact easier. School circumstances can also affect the time available for outdoor play. Some children attending special primary education described long travel times between school and home as reducing their opportunities to play outdoors. Beekhuizen et al. (2025) identified these experiences as part of time constraints. The physical school environment can also be changed to support outdoor activity and socio-emotional outcomes. Bikomeye et al. (2021) systematically reviewed six experimental studies of schoolyard greening. The interventions involved adding greenery and natural elements to schoolyards. Across the included studies, the review reported generally positive findings for physical activity and socioemotional health. However, the review included only six studies. Schoolyard greening is also a specific intervention and should not be treated as evidence that all forms of outdoor play improve children's emotional well-being. Recess provides another school setting in which children's emotional experiences have been examined directly. Poulos et al. (2026) studied 317 Year 4 and 5 children during extreme heat. Positive affect was higher after outdoor and gymnasium recess than after classroom recess. There were no significant differences in negative affect between the three settings. Poulos et al. (2026) also identified implications for school health, policy and equity. The study discussed heat-adaptive infrastructure as one way to support access to recess environments during extreme heat. However, the findings do not show that outdoor recess is always better than indoor recess because positive affect was also higher after gymnasium recess. * Schools can provide opportunities for children with and without disabilities to become familiar with one another. Beekhuizen et al. (2025) identified growing up together and making contact as interacting factors in inclusive outdoor play. Children described familiarity with other children as making contact easier. * School circumstances can also affect the time and opportunities available for outdoor play. Some children attending special primary education described long travel times between school and home as reducing the time available to play outdoors. Beekhuizen et al. (2025) identified these experiences under time constraints. * Recess provides another school setting in which children's emotional experiences have been examined. Poulos et al. (2026) studied 317 year 4 and 5 children during extreme heat weather and found significantly higher positive affect after outdoor and gymnasium recess than after classroom recess. There were no significant differences in negative affect between the three recess settings. * Poulos et al. (2026) identified implications for school health, policy and equity, including the need for heat adaptive infrastructure to support access to recess environments during extreme heat. However, the findings do not show that outdoor recess is always better than indoor recess because positive affect was also higher following gymnasium recess. {{Robelbox|theme=12|title=Quiz}} <quiz display=simple> {Children who have access to the same outdoor playground may still have different opportunities to participate in play. |type="()"} + True - False </quiz> {{Robelbox/close}} {{Robelbox|theme=12|title=Quiz}} <quiz display=simple> {Outdoor play has the same relationship with children's emotional well-being regardless of how door play or emotional well being is measured. |type="()"} - True + False </quiz> {{Robelbox/close}} {| class="wikitable" |Scenario Two primary school aged children A and B enjoy playing outdoors. They both lived near the same playground. Child A was very familiar with the playground and knows several other children who play there and easily join the games. While child B has disability, uses mobility device and does not know other children at playground. Some parts of the playground are difficult to access and joining other children who are already playing can also be challenging. Child B's parents can provide support, although the child also prefers to play more independently. Consider both children can access the same playground, but do they have same level opportunities to take part in outdoor play? |} == '''Conclusion''' == * Outdoor play and children's emotional well-being are measured in different ways across recent research. Outdoor play is not equivalent to outdoor physical activity, while emotional outcomes include emotional dysregulation, social-emotional competence, positive and negative affect, and internalising and externalising symptoms. These differences need to be considered when findings across studies are compared. * Research also provides mixed evidence about how outdoor play may be related to emotional well-being. Gross's (2015) emotion-regulation framework can be applied to emotional situations experienced during play, but it does not show that outdoor play improves emotion regulation. Lee et al. (2025) provides more direct evidence of a possible cognitive process, with working memory statistically mediating the association between afternoon outdoor play and lower emotional dysregulation. However, this observational finding does not establish causation. * Recent findings are not consistent across all outcomes or contexts. Ferguson et al. (2025) reported associations with better social-emotional competence, Dodd et al. (2026) found longitudinal associations with internalising and externalising symptom trajectories, and Poulos et al. (2026) found differences in positive but not negative affect following recess. In contrast, most associations examined by Davenport et al. (2024) were not statistically significant. * Recent findings are not consistent across all outcomes or contexts. Ferguson et al. (2025) reported associations with better social-emotional competence, Dodd et al. (2026) found longitudinal associations with internalising and externalising symptom trajectories, and Poulos et al. (2026) found differences in positive but not negative affect following recess. In contrast, most associations examined by Davenport et al. (2024) were not statistically significant. * Overall, current research supports an association between outdoor play and some aspects of children's emotional well-being but does not establish one consistent effect. Differences in measurement, research design, children and play contexts remain important when interpreting the evidence. ==See also== {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} https://www-taylorfrancis-com.ezproxy.canberra.edu.au/books/mono/10.4324/9781003349655/right-child-play-naomi-lott Book Chapter, 2 {{ic|Move to References and cite}} https://en.wikipedia.org/wiki/Emotional_dysregulation<nowiki/>- Wikipedia article {{ic|Use an internal links as shown in Tutorial 2}} https://en.wikipedia.org/wiki/Autonomy<nowiki/>- Wikipedia article {{ic|Use an internal links as shown in Tutorial 2}} https://en.wikipedia.org/wiki/Longitudinal_study<nowiki/>-Wikipedia article {{ic|Use an internal links as shown in Tutorial 2}} [[Cognitive psychology|https://en.wikiversity.org/wiki/Cognitive_psychology]]-Wikipedia article https://en.wikipedia.org/wiki/Affordance<nowiki/>-Wikipedia article {{ic|Use an internal links as shown in Tutorial 2}} ==References== {{Hanging indent|1= Beekhuizen, R. Q., Bolster, E. A. M., Gorter, J. W., Henry, N. L., Visser, K., Wittink, H., Kotte, E. M. W., Sol, M. E., & Bloemen, M. A. T. (2025). Play Together? Unveiling Facilitators and Barriers to Inclusive Outdoor Play for Dutch Children With and Without Disabilities: A Qualitative Study. Child: Care, Health & Development, 51(6), Article e70154. https://doi.org/10.1111/cch.70154 Biino, V., Pesce, C., & Martins, C. (2025). Motor Skill Development at Preschool Age in Girls and Boys: The Role of Outdoor Free Play. Children, 12(5), Article 594. https://doi.org/10.3390/children12050594 Davenport, C., Kuzik, N., Larouche, R., & Carson, V. (2025). The Associations Between Parental-Reported and Device-Based Measured Outdoor Play and Health Indicators of Physical, Cognitive, and Social–Emotional Development in Preschool-Aged Children. Pediatric Exercise Science, 37(2), 102–111. https://doi.org/10.1123/pes.2023-0119 de Lannoy, L., Barbeau, K., Seguin, N., & Tremblay, M. S. (2023). Scoping review of children’s and youth’s outdoor play publications in Canada. Chronic Diseases in Canada, 43(1), 1–13. https://doi.org/10.24095/hpcdp.43.1.01 Dodd, H. F., Cordwell, K., Hesketh, K., Johnstone, A., de la Torre-Luque, A., & McCrorie, P. (2026). Early outdoor play predicts trajectories of child mental health in a population-based cohort. Journal of Child Psychology and Psychiatry. https://doi.org/10.1111/jcpp.70175 Ferguson, M., Teyhan, A., Lovell, R., Dodd, H., Wheeler, B., & McEachan, R. (2025). The association between park visits, outdoor play and child social-emotional competency in a multi-ethnic, urban cohort. Wellbeing, Space and Society, 9, Article 100293. https://doi.org/10.1016/j.wss.2025.100293 Gross, J. J. (2015). Emotion Regulation: Current Status and Future Prospects. Psychological Inquiry, 26(1), 1–26. https://doi.org/10.1080/1047840X.2014.940781 Lee, E.-Y., de Lannoy, L., Kim, Y.-B., Rathod, A., James, M. E., Lopes, O., Nasrallah, B., Thankarajah, A., Adjei-Boadi, D., de Barros, M. I. A., Duncan, S., Miller, R. M., Mygind, L., Vanderloo, L. M., Wang, P.-Y., & Tremblay, M. S. (2025). 2025 Position statement on active outdoor play. The International Journal of Behavioral Nutrition and Physical Activity, 22(1), Article 117. https://doi.org/10.1186/s12966-025-01813-9 Lee, J. J., Flouri, E., & Jackson, Y. (2025). The Role of Timing and Amount of Outdoor Play in Emotional Dysregulation in Preschool Children. Child: Care, Health & Development, 51(1), Article e70020. https://doi.org/10.1111/cch.70020 Morgenthaler, T., Lynch, H., Loebach, J., Pentland, D., & Schulze, C. (2024). Using the Theory of Affordances to Understand Environment–Play Transactions: Environmental Taxonomy of Outdoor Play Space Features—A Scoping Review. The American Journal of Occupational Therapy, 78(4), Article 7804185120. https://doi.org/10.5014/ajot.2024.050606 Pereira, J. V., Vila-Nova, F., Veiga, G., Lopes, F., & Cordovil, R. (2024). Associations between outdoor play features and children’s behavior and health: A systematic review. Health & Place, 87, Article 103235. https://doi.org/10.1016/j.healthplace.2024.103235 Poulos, A., Hassan, U. A., Wilson, K., Price, P. M., Vanos, J., & Quilla, J. (2026). Differences in Schoolchildren’s Emotional State After Indoor Versus Outdoor Recess in Extreme‐Heat Weather. The Journal of School Health, 96(4), Article e70135. https://doi.org/10.1111/josh.70135 }} ==External links== {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} https://www.child-encyclopedia.com/outdoor-play<nowiki/>-Encyclopedia in early childhood development https://www.outdoorplaycanada.ca/wp-content/uploads/2026/03/The-2025-AOP10-Position-Statement.pdf<nowiki/>-Position Statement https://www.who.int/news/item/24-04-2019-to-grow-up-healthy-children-need-to-sit-less-and-play-more<nowiki/>-World Health Organisation [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Children]] [[Category:Motivation and emotion/Book/Nature]] [[Category:Motivation and emotion/Book/Well-being]] dgov1rsdzxlwa0o2fbt1pa8fjjcxme3 2 331308 2835435 2835141 2026-10-02T03:29:59Z U3254168 3106320 /* Social contributions */ 2835435 wikitext text/x-wiki == About me: == [[File:Relaxed female domestic cat.jpg|thumb|'''Figure 1.''' Cats are adorable companions.]] My name is Zoe Terrill. I am a third year student studying a Bachelor of Laws with a breadth major in Psychology at the [https://www.canberra.edu.au/ University of Canberra]. I am currently undertaking the course [[motivation and emotion]]. Some of my hobbies include: * Spending time with my cats * [[w:Crochet|Crocheting]] * Reading == Book chapter I'm working on == [[Motivation and emotion/Book/2026/Empathy and jury decision-making|Empathy and jury decision-making]] == Social contributions == # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FFuture_orientation_and_criminal_behaviour&diff=2823593&oldid=2767961 Edit someone's page] # [https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FGetting_started&diff=2827811&oldid=2823598 Comment on someone's page] # [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 Post on the discussion board] # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FOutdoor_play_and_children%27s_emotional_well-being&diff=2834594&oldid=2834554 Edit someone's page] # [[Talk:Motivation and emotion/Book/2026/Outdoor play and children's emotional well-being#Feedback 2|Comment on someone's page]] # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834599&oldid=2834598 Edit someone's page] # [[Talk:Motivation and emotion/Book/2026/Self-concept and motivation#Feedback|Comment on someone's page]] # [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/459237 Post on the discussion board] # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FCompetence_motivation_in_self-determination_theory&diff=2834612&oldid=2834194 Edit someone's page] # [[Talk:Motivation and emotion/Book/2026/Motivations for using sex work services#Feedback|Comment on someone's page]] #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FPerfectionism_and_procrastination&diff=2835102&oldid=2832501 Edit someone's page] #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FDark_empathy&diff=2835107&oldid=2835091 Edit someone's page] #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FMoral_disgust_and_jury_decision-making&diff=2835133&oldid=2833365 Edit someone's page] #[[Talk:Motivation and emotion/Book/2026/Gender and achievement motivation#Feedback|Comment on someone's page]] #[[c:Special:UploadWizard|Upload an image to Wikimedia Commons]] ib8cfqm6k79g6fb4o2umydt6hirfobb 2835436 2835435 2026-10-02T03:31:39Z U3254168 3106320 /* Social contributions */ 2835436 wikitext text/x-wiki == About me: == [[File:Relaxed female domestic cat.jpg|thumb|'''Figure 1.''' Cats are adorable companions.]] My name is Zoe Terrill. I am a third year student studying a Bachelor of Laws with a breadth major in Psychology at the [https://www.canberra.edu.au/ University of Canberra]. I am currently undertaking the course [[motivation and emotion]]. Some of my hobbies include: * Spending time with my cats * [[w:Crochet|Crocheting]] * Reading == Book chapter I'm working on == [[Motivation and emotion/Book/2026/Empathy and jury decision-making|Empathy and jury decision-making]] == Social contributions == # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2025%2FFuture_orientation_and_criminal_behaviour&diff=2823593&oldid=2767961 Edit someone's page] # [https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FGetting_started&diff=2827811&oldid=2823598 Comment on someone's page] # [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456345 Post on the discussion board] # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FOutdoor_play_and_children%27s_emotional_well-being&diff=2834594&oldid=2834554 Edit someone's page] # [[Talk:Motivation and emotion/Book/2026/Outdoor play and children's emotional well-being#Feedback 2|Comment on someone's page]] # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation&diff=2834599&oldid=2834598 Edit someone's page] # [[Talk:Motivation and emotion/Book/2026/Self-concept and motivation#Feedback|Comment on someone's page]] # [https://uclearn.canberra.edu.au/courses/20143/discussion_topics/459237 Post on the discussion board] # [https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FCompetence_motivation_in_self-determination_theory&diff=2834612&oldid=2834194 Edit someone's page] # [[Talk:Motivation and emotion/Book/2026/Motivations for using sex work services#Feedback|Comment on someone's page]] #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FPerfectionism_and_procrastination&diff=2835102&oldid=2832501 Edit someone's page] #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FDark_empathy&diff=2835107&oldid=2835091 Edit someone's page] #[https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion%2FBook%2F2026%2FMoral_disgust_and_jury_decision-making&diff=2835133&oldid=2833365 Edit someone's page] #[[Talk:Motivation and emotion/Book/2026/Gender and achievement motivation#Feedback|Comment on someone's page]] #[[c:Special:ListFiles/U3254168|Upload an image to Wikimedia Commons]] 90grd84rig3o3dp23agxc6zth2nk0m5 1 331340 2835461 2829995 2026-10-02T04:53:10Z U3253354 3109187 2835461 wikitext text/x-wiki == Social contribution comment == I am very interested in this topic, can't wait to see what you write! [[User:TheHutt02|TheHutt02]] ([[User talk:TheHutt02|discuss]] • [[Special:Contributions/TheHutt02|contribs]]) 03:51, 20 August 2026 (UTC) <!-- Official topic development feedback --> {{METF/2026 |1= <!-- Title --> # Title and subtitle are correctly worded and use [[w:Letter case#Sentence casing|sentence casing]] |2= <!-- Headings --> # Under-developed, [[Motivation and emotion/Assessment/Major project/Structure|1-level heading structure]] # Develop further, perhaps using a 2-level structure for larger section(s) (i.e., including subheadings) # Aim for 3 to 6 top-level headings between the Overview and Conclusion, with 3 to 5 sub-headings for large sections # Apply wiki-style headings as demonstrated in Tutorial 2 <!-- Overview--> # Good <!-- Scenario --> # A scenario or case study is presented in a feature box at the start of this section; add an image to the scenario to help attract reader interest <!-- Description --> # Add a brief, evocative description of the problem/topic <!-- Focus questions --> # Develop closer alignment between the sub-title, focus questions, and top-level headings |4= <!-- Key points--> <!-- Overall --> # Promising development # Highlight the most relevant theories and synthesise the best research on the topic # Strive for an integrated balance of the best psychological theory and research about this topic, with practical examples. <!-- Conclusion --> # Conclusion hasn't been developed # What are the practical, take-home messages? (address the focus questions) |5= <!-- Figure --> # Relevant figure(s) are presented and captioned # Consider the size and positioning (see Tutorial 2) <!-- Caption --> # Figure caption(s) provide(s) a clear, appropriately detailed description that is meaningfully connected with the main text <!-- Cite --> # Cite each figure at least once in the main text using APA style (e.g., see Figure 1) |6= <!-- Learning feature --> <!-- Interwiki links ---> # Add in-text [[m:Help:Interwiki linking|interwiki links]] for first mention of key terms to [[w:|Wikipedia]] and/or [[Motivation and emotion/Book|book chapters]] (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) <!-- Scenarios/examples/case studies --> # Consider use of more scenarios/examples/case studies <!-- Quiz --> # Several Parkinson's quiz questions doesn't really address the key messages of this topic; Parkinson's isn't really a motivational issue even though its dopamine-related # Include quiz question(s) about the take-home messages <!-- Tables --> # Also consider using tables to summarise key information |7= <!-- References --> <!-- Overall --> # Basic # Copyediting needed e.g., full journal titles, italics, full hyperlinked dois etc. <!-- Systematic reviews --> # What are the most relevant systematic reviews/meta-analyses about this topic? |8= <!-- Resources --> <!-- See also --> # See also ## Excellent <!-- External links --> # External links ## Link to the most relevant external resources about this topic |9= <!-- User page --> # Basic but effective <!-- Description about self --> # Brief description about self – consider expanding <!-- Links to profile(s) --> # Consider linking to your [https://portfolio.canberra.edu.au/ eportfolio] page and/or any other professional online profile or resume such as [https://www.linkedin.com/ LinkedIn]. This is not required, but it can be useful to interlink your professional networks. <!-- Link to book chapter --> # A link to the book chapter is provided <!-- Social contribution --> # Good – two out of three types of contributions made with direct link(s) to evidence. The other type of contribution is making: #* comments on the [[Help:Talk page|talk page]]s of other [[Motivation and emotion/Book|chapters (past or current)]] }} -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 23:02, 31 August 2026 (UTC) Hi, your focus questions are clear and give the chapter a good direction. One suggestion is to connect your headings more clearly to your focus questions. For example, the disorders section could directly address your third focus question. This could make the chapter easier to follow. [[User:U3253354|U3253354]] ([[User talk:U3253354|discuss]] • [[Special:Contributions/U3253354|contribs]]) 04:53, 2 October 2026 (UTC) 1o60zg0eijvfe9hzbakinoi3o954nj0 2835465 2835461 2026-10-02T06:07:23Z Jtneill 10242 2835465 wikitext text/x-wiki == Social contribution comment == I am very interested in this topic, can't wait to see what you write! [[User:TheHutt02|TheHutt02]] ([[User talk:TheHutt02|discuss]] • [[Special:Contributions/TheHutt02|contribs]]) 03:51, 20 August 2026 (UTC) <!-- Official topic development feedback --> {{METF/2026 |1= <!-- Title --> # Title and subtitle are correctly worded and use [[w:Letter case#Sentence casing|sentence casing]] |2= <!-- Headings --> # Under-developed, [[Motivation and emotion/Assessment/Major project/Structure|1-level heading structure]] # Develop further, perhaps using a 2-level structure for larger section(s) (i.e., including subheadings) # Aim for 3 to 6 top-level headings between the Overview and Conclusion, with 3 to 5 sub-headings for large sections # Apply wiki-style headings as demonstrated in Tutorial 2 <!-- Overview--> # Good <!-- Scenario --> # A scenario or case study is presented in a feature box at the start of this section; add an image to the scenario to help attract reader interest <!-- Description --> # Add a brief, evocative description of the problem/topic <!-- Focus questions --> # Develop closer alignment between the sub-title, focus questions, and top-level headings |4= <!-- Key points--> <!-- Overall --> # Promising development # Highlight the most relevant theories and synthesise the best research on the topic # Strive for an integrated balance of the best psychological theory and research about this topic, with practical examples. <!-- Conclusion --> # Conclusion hasn't been developed # What are the practical, take-home messages? (address the focus questions) |5= <!-- Figure --> # Relevant figure(s) are presented and captioned # Consider the size and positioning (see Tutorial 2) <!-- Caption --> # Figure caption(s) provide(s) a clear, appropriately detailed description that is meaningfully connected with the main text <!-- Cite --> # Cite each figure at least once in the main text using APA style (e.g., see Figure 1) |6= <!-- Learning feature --> <!-- Interwiki links ---> # Add in-text [[m:Help:Interwiki linking|interwiki links]] for first mention of key terms to [[w:|Wikipedia]] and/or [[Motivation and emotion/Book|book chapters]] (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) <!-- Scenarios/examples/case studies --> # Consider use of more scenarios/examples/case studies <!-- Quiz --> # Several Parkinson's quiz questions doesn't really address the key messages of this topic; Parkinson's isn't really a motivational issue even though its dopamine-related # Include quiz question(s) about the take-home messages <!-- Tables --> # Also consider using tables to summarise key information |7= <!-- References --> <!-- Overall --> # Basic # Copyediting needed e.g., full journal titles, italics, full hyperlinked dois etc. <!-- Systematic reviews --> # What are the most relevant systematic reviews/meta-analyses about this topic? |8= <!-- Resources --> <!-- See also --> # See also ## Excellent <!-- External links --> # External links ## Link to the most relevant external resources about this topic |9= <!-- User page --> # Basic but effective <!-- Description about self --> # Brief description about self – consider expanding <!-- Links to profile(s) --> # Consider linking to your [https://portfolio.canberra.edu.au/ eportfolio] page and/or any other professional online profile or resume such as [https://www.linkedin.com/ LinkedIn]. This is not required, but it can be useful to interlink your professional networks. <!-- Link to book chapter --> # A link to the book chapter is provided <!-- Social contribution --> # Good – two out of three types of contributions made with direct link(s) to evidence. The other type of contribution is making: #* comments on the [[Help:Talk page|talk page]]s of other [[Motivation and emotion/Book|chapters (past or current)]] }} -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 23:02, 31 August 2026 (UTC) ==Comment== Hi, your focus questions are clear and give the chapter a good direction. One suggestion is to connect your headings more clearly to your focus questions. For example, the disorders section could directly address your third focus question. This could make the chapter easier to follow. [[User:U3253354|U3253354]] ([[User talk:U3253354|discuss]] • [[Special:Contributions/U3253354|contribs]]) 04:53, 2 October 2026 (UTC) 1i25hhu768ybdnj3jekvvgfy7bpzv22 2 331383 2835480 2833479 2026-10-02T09:06:31Z Flickstar888 3106813 added a link to my portfolio as I do not have a linked in account 2835480 wikitext text/x-wiki == About me == My name is [[wikipedia:Felicity_(given_name)|Felicity]] (Flick) and I am a third-year Psychology student at the [https://www.canberra.edu.au/ University of Canberra]. I also hold a Bachelor of Communication majoring in Public Relations and Creative Writing from the [https://www.canberra.edu.au/ University of Canberra.] I work for the Australian Government in a communication role and last year received a certificate for 20-years' service. I am hoping to change careers and am very interested in organisational psychology. Psychology appeals to me as I find people really interesting. I have worked on many communication campaigns whereby the end goal was to change a certain behaviour or to raise awareness amongst a target audience and this experience has inevitably led me to where I am today. == My portfolio == https://portfolio.canberra.edu.au/user/view.php?id=77672. == My hobbies == [[File:Three point shoot.JPG|thumb|200x200px|'''Figure 1.''' Basketball]]In my downtime, I enjoy: * Watching basketball (see Figure 1). * Cooking * Reading non-fiction books * Travelling * Learning new things * Writing articles for Air Force News (as a RAAF Public Affairs Reservist) == Book chapter I'm working on == [[Motivation and emotion/Book/2026/Envy in the workplace|Motivation and emotion/Book/2026/Envy in the workplace - Wikiversity]] == Social contributions == #https://uclearn.canberra.edu.au/courses/20143/discussion_topics/456558?entry_id=806474 #[[Motivation and emotion/Book/2026/Developing a growth mindset|Motivation and emotion/Book/2026/Developing a growth mindset - Wikiversity]] (added a title and sub-title to the page) #https://en.wikiversity.org/w/index.php?title=Motivation_and_emotion/Book/2026/Akrasia&action=history (made edits to scenario and fixed typos) fmlwp8kznamfo32wes2rla5vumw7d91 0 331416 2835409 2834751 2026-10-02T01:33:22Z U3253354 3109187 2835409 wikitext text/x-wiki {{title|Socioemotional selectivity theory and wellbeing in ageing:<br>How do social and emotional experiences affect wellbeing as people age?}} ==Overview== {{RoundBoxTop|theme=3}}Scenario Imagine two adults at different stages of life deciding how to spend their weekend. A younger adult chooses to attend a large social event to meet new people and form new connections, while an older adult chooses to spend time with a smaller group of close family and long-term friends. Although the older adult may have a smaller social network, these relationships may provide greater emotional meaning and satisfaction (see figure 1) {{RoundBoxBottom}}'''Key question:''' Why do social priorities change as people age, and how might these changes influence emotional wellbeing? Socioemotional selectivity theory (SST) provides one explanation for why social and emotional priorities may change across adulthood. SST proposes that people's perceptions of how much time they have remaining influence the goals they prioritise. When future time is perceived as relatively indefinite, long-lasting goals tend to receive greater priority. When future time is perceived as more limited, emotionally meaningful and immediate goals become relatively more important (Carstensen et al., 1999; Carstensen, 2006). These motivational changes may help explain age-related differences in social relationships and emotional experiences. Research has found age-related differences in everyday emotional experience, including greater emotional stability with age (Carstensen et al., 2011). While a meta- analysis found evidence of an age-related positivity effect in attention and memory, although its strength varied across study conditions (Reed et al., 2014). Importantly these findings do not mean that ageing automatically leads to better emotional wellbeing. Instead, social relationships, emotional processes, individual differences, and context all need to be considered when examining wellbeing across adulthood. {{RoundBoxTop}} '''Focus questions''' {{ic|}} # What is socioemotional selectivity theory, and how does perceived future time influence motivation? # How do social relationships and priorities change across adulthood? # How does emotional experience change with age? # How can social and emotional changes influence wellbeing in older adulthood? # What are the limitations of socioemotional selectivity theory in explaining age related differences in wellbeing? {{RoundBoxBottom}} == '''Socioemotional selectivity and future time perspective''' == Socioemotional selectivity theory (SST) proposes that perceptions of future time influence motivation and the goals people prioritise (Carstensen et al., 1999). When the future is perceived as relatively open-ended, people are more likely to prioritise goals such as learning new information, exploring new opportunities, and developing relationships that may provide future benefits. In contrast, when future time is perceived as more limited, emotionally meaningful and present goals become relatively more important (Carstensen et al., 1999; Carstensen, 2006). This shift in priorities may influence the social choices people make. When future time is perceived as limited, people may become more selective about how and with who they spend their time, placing greater priority on established relationships that provide emotional meaning. From an SST perspective, changes in social relationships across adulthood may therefore reflect changing motivational priorities rather than simply a loss of interest in social interaction (Carstensen et al., 1999). Although ageing is often associated with a more limited perception of future time, SST proposes that perceived future time, rather than chronological age alone, plays an important role in shaping social and emotional goals (Carstensen et al., 1999). This distinction is important because it suggests that age-related changes in social priorities may partly reflect changes in how individuals perceive their remaining time. SST therefore provided a theoretical framework for understanding why social priorities may change across adulthood and how these changes could influence emotional experiences and wellbeing. == '''Changing social relationships across adulthood''' == Social networks change across adulthood. English and Carstensen (2014) found that social networks tended to increase during young adulthood before becoming smaller across later adulthood. Importantly, this reduction occurred primarily in more peripheral social relationships, while emotionally close relationships remained relatively stable. This suggests that smaller social networks in later adulthood do not necessarily reflect the loss of close relationships. This pattern of selective narrowing is consistent with SST. Maintaining close relationships while reducing more peripheral relationships may reflect increasing selectivity in how people use their social time as emotionally meaningful goals become relatively more important (Carstensen et al., 1999). English and Carstensen (2014) also found that older adults reported more positive and less negative emotional responses to members of their social networks, and that the emotional tone of social networks was associated with everyday emotional experience. These findings suggest that the emotional quality of social relationships may be important when considering wellbeing across adulthood. However, having a smaller social network should not automatically be interpreted as producing greater emotional wellbeing. Instead, the findings suggest that the types and emotional quality of relationships people maintain may be important for understanding social and emotional experiences in later adulthood. == '''Emotional experience and ageing''' == Emotional wellbeing does not necessarily decline with age. Carstensen et al. (2011) examined everyday emotional experiences across adulthood using an experience-sampling method, in which participants reported their emotions at randomly selected times during their daily lives. The study followed participants across multiple measurement periods over approximately 10 years, allowing the researchers to examine both age differences and changes in emotional experience over time. Carstensen et al. (2011) found that overall emotional wellbeing generally became more positive with age. However, this improvement was not unlimited, with evidence suggesting that gains levelled off in later adulthood. Emotional experiences also became more stable with age, meaning that participants showed less fluctuation in their emotional experiences across everyday life. These findings remained after the researchers accounted for several other factors that could be related to emotional experience, including personality, physical health, verbal fluency, and demographic characteristics. Emotional experience also became more complex with age. Carstensen et al. (2011) found greater co-occurrence of positive and negative emotions as people grew older, meaning that positive and negative emotions were increasingly likely to be experienced together. The researchers described this mixed emotional experience as ''poignancy''. This finding suggests that improved emotional wellbeing in later adulthood should not be interpreted as older adults simply experiencing more positive and fewer negative emotions. These findings are broadly consistent with SST because motivational priorities may help explain age-related differences in emotional experience (Carstensen et al., 1999). However, the findings do not demonstrate that ageing itself directly causes better emotional wellbeing. Instead, they provide evidence of age-related changes in several aspects of everyday emotional experience and support examining motivational changes as one possible explanation for these patterns. == '''The age-related positivity effect''' == The age-related positivity effect refers to a relative preference among older adults, compared with younger adults, for positive over negative information in attention and memory (Reed et al., 2014). From an SST perspective, changing motivational priorities may influence how emotional information is attended to and remembered. Reed et al. (2014) conducted a meta-analysis of 100 empirical studies involving 7,129 participants to examine the reliability of the positivity effect. Overall, the researchers found reliable evidence of an age-related positivity effect. Across the studies, older adults showed a greater preference for positive over negative information, whereas younger adults showed a greater preference for negative over positive information. These findings provide evidence that age-related differences in the processing of emotional information occur across a substantial body of research. However, the strength of the positivity effect varied across study conditions. Reed et al. (2014) found that the effect was larger when cognitive processing was relatively unconstrained and when studies compared groups with wider age differences. When cognitive processing was constrained by the study task, the positivity effect was smaller. This suggests that the positivity effect is not equally strong across all situations and may depend partly on the conditions under which emotional information is processed. Overall, the findings are consistent with the idea that motivational changes proposed by SST may contribute to age-related differences in attention and memory for emotional information. However, the meta-analysis does not establish that SST-related motivational changes are the sole cause of the positivity effect. Instead, it demonstrates that the effect is reliable overall while also showing that its strength varies according to methodological and sample characteristics (Reed et al., 2014). == '''Socioemotional selectivity, emotional regulation, and wellbeing''' == Taken together, the research suggests that age-related changes in social and emotional priorities may have important implications for wellbeing. Selective maintenance of close relationships (English & Carstensen, 2014), changes in everyday emotional experience (Carstensen et al., 2011), and age-related differences in attention and memory for emotional information (Reed et al., 2014) are broadly consistent with aspects of SST. Together, these findings suggest that motivational priorities, social relationships, and emotional processes may each contribute to understanding wellbeing across adulthood. However, more positive emotional experiences at older ages should not be interpreted as evidence that older adults are universally better at regulating their emotions. Isaacowitz (2022) reviewed research on ageing and emotion regulation and concluded that existing evidence does not consistently demonstrate an age-related advantage in emotion regulation. Age differences may depend on factors such as the regulation strategy being examined, characteristics of the situation, and how emotion regulation is measured. Therefore, age-related differences in emotional wellbeing cannot simply be explained by assuming that older adults possess superior emotion-regulation abilities. Overall, SST provides a framework for connecting perceived future time and motivational priorities with social and emotional experiences that may be relevant to wellbeing. However, these relationships are complex, and patterns observed across age groups do not necessarily apply equally to every individual. Understanding wellbeing in later adulthood therefore requires consideration of both the motivational processes proposed by SST and the individual and contextual factors that may influence social and emotional experience. == '''Limitations of socioemotional selectivity theory''' == Although socioemotional selectivity theory provides a useful framework for understanding age-related changes in social and emotional priorities, it does not fully explain all differences in emotional experience across adulthood. SST proposes that perceived future time influences motivational priorities (Carstensen et al., 1999), but evidence for some of the emotional patterns associated with ageing varies according to the conditions in which they are examined. For example, the age-related positivity effect is reliable overall, but its strength varies according to methodological and sample characteristics (Reed et al., 2014). This suggests that age-related emotional patterns cannot be explained by motivational priorities alone. There is also limited evidence that older adults are consistently better at regulating their emotions. Isaacowitz (2022) found that laboratory and everyday experience-sampling research does not provide consistent evidence of an age-related advantage in emotion regulation. The review also highlights the importance of considering individual differences and context when examining changes in emotion regulation across adulthood. Therefore, although SST offers an important explanation for how perceptions of time may shape social and emotional priorities, it should not be interpreted as a complete explanation of emotional wellbeing in later adulthood (Isaacowitz, 2022). ==Figures== {| class="wikitable" |+ !Perceived future time !Goals receiving relatively greater priority |- |More open-ended |Learning, exploring, new opportunities, and relationships that may provide future benefits |- |More limited |Present and emotionally meaningful goals and relationships |} [[File:Representaciones de los adultos mayores.jpg|thumb|270x270px|Figure 1. Older adults spending time together. Socioemotional selectivity theory proposes that emotionally meaningful relationships may receive greater priority when future time is perceived as limited.]] ==Learning features== {{RoundBoxTop|theme=}}{{RoundBoxTop|theme=3}} '''Case Study: Changing social priorities''' Maria is 65 and increasingly prefers spending time with close friends and family rather than attending large social gatherings. Questions #How could SST explain Maria's changing social preferences? #Does Maria's smaller social network necessarily indicate greater emotional wellbeing? Why or why not?{{RoundBoxBottom}} {{RoundBoxTop|theme=3}} '''Test your knowledge''' '''1. According to SST, what is most important for understanding changes in motivational priorities?''' A. Chronological age alone<br> B. Perceived future time<br> C. Number of social relationships<br> D. Personality alone '''Answer:''' B. Perceived future time '''2. What does research suggest commonly happens to social networks across later adulthood?''' A. All relationships decline equally<br> B. Close relationships disappear first<br> C. More peripheral relationships tend to decline while close relationships remain relatively stable<br> D. Social networks always become larger '''Answer:''' C. More peripheral relationships tend to decline while close relationships remain relatively stable '''3. Which statement best reflects the evidence discussed in this chapter?''' A. Older adults are always better at regulating their emotions<br> B. Ageing automatically improves emotional wellbeing<br> C. The positivity effect is equally strong in all situations<br> D. Age-related social and emotional patterns can vary across individuals and situations '''Answer:''' D. Age-related social and emotional patterns can vary across individuals and situations {{RoundBoxBottom}} ==Conclusion== Socioemotional selectivity theory provides a framework for understanding how changing perceptions of future time may influence social and emotional priorities across adulthood. As future time is perceived as more limited, emotionally meaningful goals and relationships tend to become relatively more important (Carstensen et al., 1999). Consistent with this framework, research suggests that social networks may become more selective across adulthood, with close relationships remaining relatively stable while more minor relationships decline (English & Carstensen, 2014). Emotional wellbeing also does not necessarily decline with age. Research indicates age-related changes in everyday emotional experience, including greater emotional stability, as well as differences in attention and memory for positive and negative information (Carstensen et al., 2011; Reed et al., 2014). However, these patterns do not mean that ageing automatically leads to better emotional regulation or greater wellbeing. Instead, the evidence suggests that social relationships, motivational priorities, emotional process, and individual and contextual factors all need to be considered when understanding wellbeing across adulthood (Isaacowitz, 2022). Overall, SST helps explain how changing social and emotional priorities may be relevant to wellbeing in later adulthood, while recognising that chronological age alone does not determine emotional wellbeing. ==See also== ** [https://en.wikipedia.org/wiki/Socioemotional_selectivity_theory? Socioemotional selectivity theory] (Wikipedia) ** [[Emotional self-regulation|Emotion]] (Wikiversity) ==References== {{Hanging indent|1= Carstensen, L. L. (2006). The influence of a sense of time on human development. ''Science, 312''(5782), 1913–1915. https://doi.org/10.1126/science.1127488 Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999). Taking time seriously: A theory of socioemotional selectivity. ''American Psychologist, 54''(3), 165–181. https://doi.org/10.1037/0003-066X.54.3.165 Carstensen, L. L., Turan, B., Scheibe, S., Ram, N., Ersner-Hershfield, H., Samanez-Larkin, G. R., Brooks, K. P., & Nesselroade, J. R. (2011). Emotional experience improves with age: Evidence based on over 10 years of experience sampling. ''Psychology and Aging, 26''(1), 21–33. https://doi.org/10.1037/a0021285 English, T., & Carstensen, L. L. (2014). Selective narrowing of social networks across adulthood is associated with improved emotional experience in daily life. ''International Journal of Behavioral Development'', ''38''(2), 195–202. https://doi.org/10.1177/0165025413515404 Isaacowitz, D. M. (2022). What do we know about aging and emotion regulation? ''Perspectives on Psychological Science'', ''17''(6), 174569162110598. https://doi.org/10.1177/17456916211059819 Reed, A. E., Chan, L., & Mikels, J. A. (2014). Meta-analysis of the age-related positivity effect: Age differences in preferences for positive over negative information. ''Psychology and Aging, 29''(1), 1–15. https://doi.org/10.1037/a0035194 }} ==External links== * [https://www.apa.org/news/press/releases/2019/11/older-adults-social-networks American Psychological Association - Older adults and social wellbeing] * [https://lifespan.stanford.edu/research?utm_source Stanford Life-span Development Laboratory – Socioemotional selectivity theory] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Ageing]] [[Category:Motivation and emotion/Book/Emotion]] [[Category:Motivation and emotion/Book/Social]] fxbpkgd938clh6ozhozgb7eib0ditzl 2835432 2835409 2026-10-02T03:22:28Z U3253354 3109187 2835432 wikitext text/x-wiki {{title|Socioemotional selectivity theory and wellbeing in ageing:<br>How do social and emotional experiences affect wellbeing as people age?}} ==Overview== {{RoundBoxTop|theme=3}}Scenario Imagine two adults at different stages of life deciding how to spend their weekend. A younger adult chooses to attend a large social event to meet new people and form new connections, while an older adult chooses to spend time with a smaller group of close family and long-term friends. Although the older adult may have a smaller social network, these relationships may provide greater emotional meaning and satisfaction (see figure 1) {{RoundBoxBottom}}'''Key question:''' Why do social priorities change as people age, and how might these changes influence emotional wellbeing? Socioemotional selectivity theory (SST) provides one explanation for why social and emotional priorities may change across adulthood. SST proposes that people's perceptions of how much time they have remaining influence the goals they prioritise. When future time is perceived as relatively indefinite, long-lasting goals tend to receive greater priority. When future time is perceived as more limited, emotionally meaningful and immediate goals become relatively more important (Carstensen et al., 1999; Carstensen, 2006). These motivational changes may help explain age-related differences in social relationships and emotional experiences. Research has found age-related differences in everyday emotional experience, including greater emotional stability with age (Carstensen et al., 2011). While a meta- analysis found evidence of an age-related positivity effect in attention and memory, although its strength varied across study conditions (Reed et al., 2014). Importantly these findings do not mean that ageing automatically leads to better emotional wellbeing. Instead, social relationships, emotional processes, individual differences, and context all need to be considered when examining wellbeing across adulthood. {{RoundBoxTop}} '''Focus questions''' {{ic|}} # What is socioemotional selectivity theory, and how does perceived future time influence motivation? # How do social relationships and priorities change across adulthood? # How does emotional experience change with age? # How can social and emotional changes influence wellbeing in older adulthood? # What are the limitations of socioemotional selectivity theory in explaining age related differences in wellbeing? {{RoundBoxBottom}} == '''Socioemotional selectivity and future time perspective''' == Socioemotional selectivity theory (SST) proposes that perceptions of future time influence motivation and the goals people prioritise (Carstensen et al., 1999). When the future is perceived as relatively open-ended, people are more likely to prioritise goals such as learning new information, exploring new opportunities, and developing relationships that may provide future benefits. In contrast, when future time is perceived as more limited, emotionally meaningful and present goals become relatively more important (Carstensen et al., 1999; Carstensen, 2006). This shift in priorities may influence the social choices people make. When future time is perceived as limited, people may become more selective about how and with whom they spend their time, placing greater priority on established relationships that provide emotional meaning. From an SST perspective, changes in social relationships across adulthood may therefore reflect changing motivational priorities rather than simply a loss of interest in social interaction (Carstensen et al., 1999). Although ageing is often associated with a more limited perception of future time, SST proposes that perceived future time, rather than chronological age alone, plays an important role in shaping social and emotional goals (Carstensen et al., 1999). This distinction is important because it suggests that age-related changes in social priorities may partly reflect changes in how individuals perceive their remaining time. SST therefore provides a theoretical framework for understanding why social priorities may change across adulthood and how these changes could influence emotional experiences and wellbeing. == '''Changing social relationships across adulthood''' == Social networks change across adulthood. English and Carstensen (2014) found that social networks tended to increase during young adulthood before becoming smaller across later adulthood. Importantly, this reduction occurred primarily in more peripheral social relationships, while emotionally close relationships remained relatively stable. This suggests that smaller social networks in later adulthood do not necessarily reflect the loss of close relationships. This pattern of selective narrowing is consistent with SST. Maintaining close relationships while reducing more peripheral relationships may reflect increasing selectivity in how people use their social time as emotionally meaningful goals become relatively more important (Carstensen et al., 1999). English and Carstensen (2014) also found that older adults reported more positive and less negative emotional responses to members of their social networks, and that the emotional tone of social networks was associated with everyday emotional experience. These findings suggest that the emotional quality of social relationships may be important when considering wellbeing across adulthood. However, having a smaller social network should not automatically be interpreted as producing greater emotional wellbeing. Instead, the findings suggest that the types and emotional quality of relationships people maintain may be important for understanding social and emotional experiences in later adulthood. == '''Emotional experience and ageing''' == Emotional wellbeing does not necessarily decline with age. Carstensen et al. (2011) examined everyday emotional experiences across adulthood using an experience-sampling method, in which participants reported their emotions at randomly selected times during their daily lives. The study followed participants across multiple measurement periods over approximately 10 years, allowing the researchers to examine both age differences and changes in emotional experience over time. Carstensen et al. (2011) found that overall emotional wellbeing generally became more positive with age. However, this improvement was not unlimited, with evidence suggesting that gains levelled off in later adulthood. Emotional experiences also became more stable with age, meaning that participants showed less fluctuation in their emotional experiences across everyday life. These findings remained after the researchers accounted for several other factors that could be related to emotional experience, including personality, physical health, verbal fluency, and demographic characteristics. Emotional experience also became more complex with age. Carstensen et al. (2011) found greater co-occurrence of positive and negative emotions as people grew older, meaning that positive and negative emotions were increasingly likely to be experienced together. The researchers described this mixed emotional experience as ''poignancy''. This finding suggests that improved emotional wellbeing in later adulthood should not be interpreted as older adults simply experiencing more positive and fewer negative emotions. These findings are broadly consistent with SST because motivational priorities may help explain age-related differences in emotional experience (Carstensen et al., 1999). However, the findings do not demonstrate that ageing itself directly causes better emotional wellbeing. Instead, they provide evidence of age-related changes in several aspects of everyday emotional experience and support examining motivational changes as one possible explanation for these patterns. == '''The age-related positivity effect''' == The age-related positivity effect refers to a relative preference among older adults, compared with younger adults, for positive over negative information in attention and memory (Reed et al., 2014). From an SST perspective, changing motivational priorities may influence how emotional information is attended to and remembered. Reed et al. (2014) conducted a meta-analysis of 100 empirical studies involving 7,129 participants to examine the reliability of the positivity effect. Overall, the researchers found reliable evidence of an age-related positivity effect. Across the studies, older adults showed a greater preference for positive over negative information, whereas younger adults showed a greater preference for negative over positive information. These findings provide evidence that age-related differences in the processing of emotional information occur across a substantial body of research. However, the strength of the positivity effect varied across study conditions. Reed et al. (2014) found that the effect was larger when cognitive processing was relatively unconstrained and when studies compared groups with wider age differences. When cognitive processing was constrained by the study task, the positivity effect was smaller. This suggests that the positivity effect is not equally strong across all situations and may depend partly on the conditions under which emotional information is processed. Overall, the findings are consistent with the idea that motivational changes proposed by SST may contribute to age-related differences in attention and memory for emotional information. However, the meta-analysis does not establish that SST-related motivational changes are the sole cause of the positivity effect. Instead, it demonstrates that the effect is reliable overall while also showing that its strength varies according to methodological and sample characteristics (Reed et al., 2014). == '''Socioemotional selectivity, emotional regulation, and wellbeing''' == Taken together, the research suggests that age-related changes in social and emotional priorities may have important implications for wellbeing. Selective maintenance of close relationships (English & Carstensen, 2014), changes in everyday emotional experience (Carstensen et al., 2011), and age-related differences in attention and memory for emotional information (Reed et al., 2014) are broadly consistent with aspects of SST. Together, these findings suggest that motivational priorities, social relationships, and emotional processes may each contribute to understanding wellbeing across adulthood. However, more positive emotional experiences at older ages should not be interpreted as evidence that older adults are universally better at regulating their emotions. Isaacowitz (2022) reviewed research on ageing and emotion regulation and concluded that existing evidence does not consistently demonstrate an age-related advantage in emotion regulation. Age differences may depend on factors such as the regulation strategy being examined, characteristics of the situation, and how emotion regulation is measured. Therefore, age-related differences in emotional wellbeing cannot simply be explained by assuming that older adults possess superior emotion-regulation abilities. Overall, SST provides a framework for connecting perceived future time and motivational priorities with social and emotional experiences that may be relevant to wellbeing. However, these relationships are complex, and patterns observed across age groups do not necessarily apply equally to every individual. Understanding wellbeing in later adulthood therefore requires consideration of both the motivational processes proposed by SST and the individual and contextual factors that may influence social and emotional experience. == '''Limitations of socioemotional selectivity theory''' == Although socioemotional selectivity theory provides a useful framework for understanding age-related changes in social and emotional priorities, it does not fully explain all differences in emotional experience across adulthood. SST proposes that perceived future time influences motivational priorities (Carstensen et al., 1999), but evidence for some of the emotional patterns associated with ageing varies according to the conditions in which they are examined. For example, the age-related positivity effect is reliable overall, but its strength varies according to methodological and sample characteristics (Reed et al., 2014). This suggests that age-related emotional patterns cannot be explained by motivational priorities alone. There is also limited evidence that older adults are consistently better at regulating their emotions. Isaacowitz (2022) found that laboratory and everyday experience-sampling research does not provide consistent evidence of an age-related advantage in emotion regulation. The review also highlights the importance of considering individual differences and context when examining changes in emotion regulation across adulthood. Therefore, although SST offers an important explanation for how perceptions of time may shape social and emotional priorities, it should not be interpreted as a complete explanation of emotional wellbeing in later adulthood (Isaacowitz, 2022). ==Figures== {| class="wikitable" |+ !Perceived future time !Goals receiving relatively greater priority |- |More open-ended |Learning, exploring, new opportunities, and relationships that may provide future benefits |- |More limited |Present and emotionally meaningful goals and relationships |} [[File:Representaciones de los adultos mayores.jpg|thumb|270x270px|Figure 1. Older adults spending time together. Socioemotional selectivity theory proposes that emotionally meaningful relationships may receive greater priority when future time is perceived as limited.]] ==Learning features== {{RoundBoxTop|theme=}}{{RoundBoxTop|theme=3}} '''Case Study: Changing social priorities''' Maria is 65 and increasingly prefers spending time with close friends and family rather than attending large social gatherings. Questions #How could SST explain Maria's changing social preferences? #Does Maria's smaller social network necessarily indicate greater emotional wellbeing? Why or why not?{{RoundBoxBottom}} {{RoundBoxTop|theme=3}} '''Test your knowledge''' '''1. According to SST, what is most important for understanding changes in motivational priorities?''' A. Chronological age alone<br> B. Perceived future time<br> C. Number of social relationships<br> D. Personality alone '''Answer:''' B. Perceived future time '''2. What does research suggest commonly happens to social networks across later adulthood?''' A. All relationships decline equally<br> B. Close relationships disappear first<br> C. More peripheral relationships tend to decline while close relationships remain relatively stable<br> D. Social networks always become larger '''Answer:''' C. More peripheral relationships tend to decline while close relationships remain relatively stable '''3. Which statement best reflects the evidence discussed in this chapter?''' A. Older adults are always better at regulating their emotions<br> B. Ageing automatically improves emotional wellbeing<br> C. The positivity effect is equally strong in all situations<br> D. Age-related social and emotional patterns can vary across individuals and situations '''Answer:''' D. Age-related social and emotional patterns can vary across individuals and situations {{RoundBoxBottom}} ==Conclusion== Socioemotional selectivity theory provides a framework for understanding how changing perceptions of future time may influence social and emotional priorities across adulthood. As future time is perceived as more limited, emotionally meaningful goals and relationships tend to become relatively more important (Carstensen et al., 1999). Consistent with this framework, research suggests that social networks may become more selective across adulthood, with close relationships remaining relatively stable while more minor relationships decline (English & Carstensen, 2014). Emotional wellbeing also does not necessarily decline with age. Research indicates age-related changes in everyday emotional experience, including greater emotional stability, as well as differences in attention and memory for positive and negative information (Carstensen et al., 2011; Reed et al., 2014). However, these patterns do not mean that ageing automatically leads to better emotional regulation or greater wellbeing. Instead, the evidence suggests that social relationships, motivational priorities, emotional process, and individual and contextual factors all need to be considered when understanding wellbeing across adulthood (Isaacowitz, 2022). Overall, SST helps explain how changing social and emotional priorities may be relevant to wellbeing in later adulthood, while recognising that chronological age alone does not determine emotional wellbeing. ==See also== ** [https://en.wikipedia.org/wiki/Socioemotional_selectivity_theory? Socioemotional selectivity theory] (Wikipedia) ** [[Emotional self-regulation|Emotion]] (Wikiversity) ==References== {{Hanging indent|1= Carstensen, L. L. (2006). The influence of a sense of time on human development. ''Science, 312''(5782), 1913–1915. https://doi.org/10.1126/science.1127488 Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999). Taking time seriously: A theory of socioemotional selectivity. ''American Psychologist, 54''(3), 165–181. https://doi.org/10.1037/0003-066X.54.3.165 Carstensen, L. L., Turan, B., Scheibe, S., Ram, N., Ersner-Hershfield, H., Samanez-Larkin, G. R., Brooks, K. P., & Nesselroade, J. R. (2011). Emotional experience improves with age: Evidence based on over 10 years of experience sampling. ''Psychology and Aging, 26''(1), 21–33. https://doi.org/10.1037/a0021285 English, T., & Carstensen, L. L. (2014). Selective narrowing of social networks across adulthood is associated with improved emotional experience in daily life. ''International Journal of Behavioral Development'', ''38''(2), 195–202. https://doi.org/10.1177/0165025413515404 Isaacowitz, D. M. (2022). What do we know about aging and emotion regulation? ''Perspectives on Psychological Science'', ''17''(6), 174569162110598. https://doi.org/10.1177/17456916211059819 Reed, A. E., Chan, L., & Mikels, J. A. (2014). Meta-analysis of the age-related positivity effect: Age differences in preferences for positive over negative information. ''Psychology and Aging, 29''(1), 1–15. https://doi.org/10.1037/a0035194 }} ==External links== * [https://www.apa.org/news/press/releases/2019/11/older-adults-social-networks American Psychological Association - Older adults and social wellbeing] * [https://lifespan.stanford.edu/research?utm_source Stanford Life-span Development Laboratory – Socioemotional selectivity theory] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Ageing]] [[Category:Motivation and emotion/Book/Emotion]] [[Category:Motivation and emotion/Book/Social]] r2sgjrxwqpx3nthxbaosf7y61emuwf7 2835433 2835432 2026-10-02T03:24:46Z U3253354 3109187 2835433 wikitext text/x-wiki {{title|Socioemotional selectivity theory and wellbeing in ageing:<br>How do social and emotional experiences affect wellbeing as people age?}} ==Overview== {{RoundBoxTop|theme=3}}Scenario Imagine two adults at different stages of life deciding how to spend their weekend. A younger adult chooses to attend a large social event to meet new people and form new connections, while an older adult chooses to spend time with a smaller group of close family and long-term friends. Although the older adult may have a smaller social network, these relationships may provide greater emotional meaning and satisfaction (see figure 1) {{RoundBoxBottom}}'''Key question:''' Why do social priorities change as people age, and how might these changes influence emotional wellbeing? Socioemotional selectivity theory (SST) provides one explanation for why social and emotional priorities may change across adulthood. SST proposes that people's perceptions of how much time they have remaining influence the goals they prioritise. When future time is perceived as relatively indefinite, long-lasting goals tend to receive greater priority. When future time is perceived as more limited, emotionally meaningful and immediate goals become relatively more important (Carstensen et al., 1999; Carstensen, 2006). These motivational changes may help explain age-related differences in social relationships and emotional experiences. Research has found age-related differences in everyday emotional experience, including greater emotional stability with age (Carstensen et al., 2011). While a meta- analysis found evidence of an age-related positivity effect in attention and memory, although its strength varied across study conditions (Reed et al., 2014). Importantly these findings do not mean that ageing automatically leads to better emotional wellbeing. Instead, social relationships, emotional processes, individual differences, and context all need to be considered when examining wellbeing across adulthood. {{RoundBoxTop}} '''Focus questions''' {{ic|}} # What is socioemotional selectivity theory, and how does perceived future time influence motivation? # How do social relationships and priorities change across adulthood? # How does emotional experience change with age? # How can social and emotional changes influence wellbeing in older adulthood? # What are the limitations of socioemotional selectivity theory in explaining age related differences in wellbeing? {{RoundBoxBottom}} == '''Socioemotional selectivity and future time perspective''' == Socioemotional selectivity theory (SST) proposes that perceptions of future time influence motivation and the goals people prioritise (Carstensen et al., 1999). When the future is perceived as relatively open-ended, people are more likely to prioritise goals such as learning new information, exploring new opportunities, and developing relationships that may provide future benefits. In contrast, when future time is perceived as more limited, emotionally meaningful and present goals become relatively more important (Carstensen et al., 1999; Carstensen, 2006). This shift in priorities may influence the social choices people make. When future time is perceived as limited, people may become more selective about how and with whom they spend their time, placing greater priority on established relationships that provide emotional meaning. From an SST perspective, changes in social relationships across adulthood may therefore reflect changing motivational priorities rather than simply a loss of interest in social interaction (Carstensen et al., 1999). Although ageing is often associated with a more limited perception of future time, SST proposes that perceived future time, rather than chronological age alone, plays an important role in shaping social and emotional goals (Carstensen et al., 1999). This distinction is important because it suggests that age-related changes in social priorities may partly reflect changes in how individuals perceive their remaining time. SST therefore provides a theoretical framework for understanding why social priorities may change across adulthood and how these changes could influence emotional experiences and wellbeing. == '''Changing social relationships across adulthood''' == Social networks change across adulthood. English and Carstensen (2014) found that social networks tended to increase during young adulthood before becoming smaller across later adulthood. Importantly, this reduction occurred primarily in more peripheral social relationships, while emotionally close relationships remained relatively stable. This suggests that smaller social networks in later adulthood do not necessarily reflect the loss of close relationships. This pattern of selective narrowing is consistent with SST. Maintaining close relationships while reducing more peripheral relationships may reflect increasing selectivity in how people use their social time as emotionally meaningful goals become relatively more important (Carstensen et al., 1999). English and Carstensen (2014) also found that older adults reported more positive and less negative emotional responses to members of their social networks, and that the emotional tone of social networks was associated with everyday emotional experience. These findings suggest that the emotional quality of social relationships may be important when considering wellbeing across adulthood. However, having a smaller social network should not automatically be interpreted as producing greater emotional wellbeing. Instead, the findings suggest that the types and emotional quality of relationships people maintain may be important for understanding social and emotional experiences in later adulthood. == '''Emotional experience and ageing''' == Emotional wellbeing does not necessarily decline with age. Carstensen et al. (2011) examined everyday emotional experiences across adulthood using an experience-sampling method, in which participants reported their emotions at randomly selected times during their daily lives. The study followed participants across multiple measurement periods over approximately 10 years, allowing the researchers to examine both age differences and changes in emotional experience over time. Carstensen et al. (2011) found that overall emotional wellbeing generally became more positive with age. However, this improvement was not unlimited, with evidence suggesting that gains levelled off in later adulthood. Emotional experiences also became more stable with age, meaning that participants showed less fluctuation in their emotional experiences across everyday life. These findings remained after the researchers accounted for several other factors that could be related to emotional experience, including personality, physical health, verbal fluency, and demographic characteristics. Emotional experience also became more complex with age. Carstensen et al. (2011) found greater co-occurrence of positive and negative emotions as people grew older, meaning that positive and negative emotions were increasingly likely to be experienced together. The researchers described this mixed emotional experience as ''poignancy''. This finding suggests that improved emotional wellbeing in later adulthood should not be interpreted as older adults simply experiencing more positive and fewer negative emotions. These findings are broadly consistent with SST because motivational priorities may help explain age-related differences in emotional experience (Carstensen et al., 1999). However, the findings do not demonstrate that ageing itself directly causes better emotional wellbeing. Instead, they provide evidence of age-related changes in several aspects of everyday emotional experience and support examining motivational changes as one possible explanation for these patterns. == '''The age-related positivity effect''' == The age-related positivity effect refers to a relative preference among older adults, compared with younger adults, for positive over negative information in attention and memory (Reed et al., 2014). From an SST perspective, changing motivational priorities may influence how emotional information is attended to and remembered. Reed et al. (2014) conducted a meta-analysis of 100 empirical studies involving 7,129 participants to examine the reliability of the positivity effect. Overall, the researchers found reliable evidence of an age-related positivity effect. Across the studies, older adults showed a greater preference for positive over negative information, whereas younger adults showed a greater preference for negative over positive information. These findings provide evidence that age-related differences in the processing of emotional information occur across a substantial body of research. However, the strength of the positivity effect varied across study conditions. Reed et al. (2014) found that the effect was larger when cognitive processing was relatively unconstrained and when studies compared groups with wider age differences. When cognitive processing was constrained by the study task, the positivity effect was smaller. This suggests that the positivity effect is not equally strong across all situations and may depend partly on the conditions under which emotional information is processed. Overall, the findings are consistent with the idea that motivational changes proposed by SST may contribute to age-related differences in attention and memory for emotional information. However, the meta-analysis does not establish that SST-related motivational changes are the sole cause of the positivity effect. Instead, it demonstrates that the effect is reliable overall while also showing that its strength varies according to methodological and sample characteristics (Reed et al., 2014). == '''Socioemotional selectivity, emotional regulation, and wellbeing''' == Taken together, the research suggests that age-related changes in social and emotional priorities may have important implications for wellbeing. Selective maintenance of close relationships (English & Carstensen, 2014), changes in everyday emotional experience (Carstensen et al., 2011), and age-related differences in attention and memory for emotional information (Reed et al., 2014) are broadly consistent with aspects of SST. Together, these findings suggest that motivational priorities, social relationships, and emotional processes may each contribute to understanding wellbeing across adulthood. However, more positive emotional experiences at older ages should not be interpreted as evidence that older adults are universally better at regulating their emotions. Isaacowitz (2022) reviewed research on ageing and emotion regulation and concluded that existing evidence does not consistently demonstrate an age-related advantage in emotion regulation. Age differences may depend on factors such as the regulation strategy being examined, characteristics of the situation, and how emotion regulation is measured. Therefore, age-related differences in emotional wellbeing cannot simply be explained by assuming that older adults possess superior emotion-regulation abilities. Overall, SST provides a framework for connecting perceived future time and motivational priorities with social and emotional experiences that may be relevant to wellbeing. However, these relationships are complex, and patterns observed across age groups do not necessarily apply equally to every individual. Understanding wellbeing in later adulthood therefore requires consideration of both the motivational processes proposed by SST and the individual and contextual factors that may influence social and emotional experience. == '''Limitations of socioemotional selectivity theory''' == Although socioemotional selectivity theory provides a useful framework for understanding age-related changes in social and emotional priorities, it does not fully explain all differences in emotional experience across adulthood. SST proposes that perceived future time influences motivational priorities (Carstensen et al., 1999), but evidence for some of the emotional patterns associated with ageing varies according to the conditions in which they are examined. For example, the age-related positivity effect is reliable overall, but its strength varies according to methodological and sample characteristics (Reed et al., 2014). This suggests that age-related emotional patterns cannot be explained by motivational priorities alone. There is also limited evidence that older adults are consistently better at regulating their emotions. Isaacowitz (2022) found that laboratory and everyday experience-sampling research does not provide consistent evidence of an age-related advantage in emotion regulation. The review also highlights the importance of considering individual differences and context when examining changes in emotion regulation across adulthood. Therefore, although SST offers an important explanation for how perceptions of time may shape social and emotional priorities, it should not be interpreted as a complete explanation of emotional wellbeing in later adulthood (Isaacowitz, 2022). ==Figures== {| class="wikitable" |+ !Perceived future time !Goals receiving relatively greater priority |- |More open-ended |Learning, exploring, new opportunities, and relationships that may provide future benefits |- |More limited |Present and emotionally meaningful goals and relationships |} [[File:Representaciones de los adultos mayores.jpg|thumb|270x270px|Figure 1. Older adults spending time together. Socioemotional selectivity theory proposes that emotionally meaningful relationships may receive greater priority when future time is perceived as limited.]] ==Learning features== {{RoundBoxTop|theme=}}{{RoundBoxTop|theme=3}} '''Case Study: Changing social priorities''' Maria is 65 and increasingly prefers spending time with close friends and family rather than attending large social gatherings. Questions #How could SST explain Maria's changing social preferences? #Does Maria's smaller social network necessarily indicate greater emotional wellbeing? Why or why not?{{RoundBoxBottom}} {{RoundBoxTop|theme=3}} '''Test your knowledge''' '''1. According to SST, what is most important for understanding changes in motivational priorities?''' A. Chronological age alone<br> B. Perceived future time<br> C. Number of social relationships<br> D. Personality alone '''Answer:''' B. Perceived future time '''2. What does research suggest commonly happens to social networks across later adulthood?''' A. All relationships decline equally<br> B. Close relationships disappear first<br> C. More peripheral relationships tend to decline while close relationships remain relatively stable<br> D. Social networks always become larger '''Answer:''' C. More peripheral relationships tend to decline while close relationships remain relatively stable '''3. Which statement best reflects the evidence discussed in this chapter?''' A. Older adults are always better at regulating their emotions<br> B. Ageing automatically improves emotional wellbeing<br> C. The positivity effect is equally strong in all situations<br> D. Age-related social and emotional patterns can vary across individuals and situations '''Answer:''' D. Age-related social and emotional patterns can vary across individuals and situations {{RoundBoxBottom}} ==Conclusion== Socioemotional selectivity theory provides a framework for understanding how changing perceptions of future time may influence social and emotional priorities across adulthood. As future time is perceived as more limited, emotionally meaningful goals and relationships tend to become relatively more important (Carstensen et al., 1999). Consistent with this framework, research suggests that social networks may become more selective across adulthood, with close relationships remaining relatively stable while more minor relationships decline (English & Carstensen, 2014). Emotional wellbeing also does not necessarily decline with age. Research indicates age-related changes in everyday emotional experience, including greater emotional stability, as well as differences in attention and memory for positive and negative information (Carstensen et al., 2011; Reed et al., 2014). However, these patterns do not mean that ageing automatically leads to better emotional regulation or greater wellbeing. Instead, the evidence suggests that social relationships, motivational priorities, emotional processes, and individual and contextual factors all need to be considered when understanding wellbeing across adulthood (Isaacowitz, 2022). Overall, SST helps explain how changing social and emotional priorities may be relevant to wellbeing in later adulthood, while recognising that chronological age alone does not determine emotional wellbeing. ==See also== ** [https://en.wikipedia.org/wiki/Socioemotional_selectivity_theory? Socioemotional selectivity theory] (Wikipedia) ** [[Emotional self-regulation|Emotion]] (Wikiversity) ==References== {{Hanging indent|1= Carstensen, L. L. (2006). The influence of a sense of time on human development. ''Science, 312''(5782), 1913–1915. https://doi.org/10.1126/science.1127488 Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999). Taking time seriously: A theory of socioemotional selectivity. ''American Psychologist, 54''(3), 165–181. https://doi.org/10.1037/0003-066X.54.3.165 Carstensen, L. L., Turan, B., Scheibe, S., Ram, N., Ersner-Hershfield, H., Samanez-Larkin, G. R., Brooks, K. P., & Nesselroade, J. R. (2011). Emotional experience improves with age: Evidence based on over 10 years of experience sampling. ''Psychology and Aging, 26''(1), 21–33. https://doi.org/10.1037/a0021285 English, T., & Carstensen, L. L. (2014). Selective narrowing of social networks across adulthood is associated with improved emotional experience in daily life. ''International Journal of Behavioral Development'', ''38''(2), 195–202. https://doi.org/10.1177/0165025413515404 Isaacowitz, D. M. (2022). What do we know about aging and emotion regulation? ''Perspectives on Psychological Science'', ''17''(6), 174569162110598. https://doi.org/10.1177/17456916211059819 Reed, A. E., Chan, L., & Mikels, J. A. (2014). Meta-analysis of the age-related positivity effect: Age differences in preferences for positive over negative information. ''Psychology and Aging, 29''(1), 1–15. https://doi.org/10.1037/a0035194 }} ==External links== * [https://www.apa.org/news/press/releases/2019/11/older-adults-social-networks American Psychological Association - Older adults and social wellbeing] * [https://lifespan.stanford.edu/research?utm_source Stanford Life-span Development Laboratory – Socioemotional selectivity theory] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Ageing]] [[Category:Motivation and emotion/Book/Emotion]] [[Category:Motivation and emotion/Book/Social]] 77wts67z9npglzkgwg1gswmpk54m1em 2835458 2835433 2026-10-02T04:19:04Z U3253354 3109187 2835458 wikitext text/x-wiki {{title|Socioemotional selectivity theory and wellbeing in ageing:<br>How do social and emotional experiences affect wellbeing as people age?}} ==Overview== {{RoundBoxTop|theme=3}}Scenario Imagine two adults at different stages of life deciding how to spend their weekend. A younger adult chooses to attend a large social event to meet new people and form new connections, while an older adult chooses to spend time with a smaller group of close family and long-term friends. Although the older adult may have a smaller social network, these relationships may provide greater emotional meaning and satisfaction (see figure 1) {{RoundBoxBottom}}'''Key question:''' Why do social priorities change as people age, and how might these changes influence emotional wellbeing? Socioemotional selectivity theory (SST) provides one explanation for why social and emotional priorities may change across adulthood. SST proposes that people's perceptions of how much time they have remaining influence the goals they prioritise. When future time is perceived as relatively indefinite, long-lasting goals tend to receive greater priority. When future time is perceived as more limited, emotionally meaningful and immediate goals become relatively more important (Carstensen et al., 1999; Carstensen, 2006). These motivational changes may help explain age-related differences in social relationships and emotional experiences. Research has found age-related differences in everyday emotional experience, including greater emotional stability with age (Carstensen et al., 2011). While a meta- analysis found evidence of an age-related positivity effect in attention and memory, although its strength varied across study conditions (Reed et al., 2014). Importantly these findings do not mean that ageing automatically leads to better emotional wellbeing. Instead, social relationships, emotional processes, individual differences, and context all need to be considered when examining wellbeing across adulthood. {{RoundBoxTop}} '''Focus questions''' {{ic|}} # What is socioemotional selectivity theory, and how does perceived future time influence motivation? # How do social relationships and priorities change across adulthood? # How does emotional experience change with age? # How can social and emotional changes influence wellbeing in older adulthood? # What are the limitations of socioemotional selectivity theory in explaining age related differences in wellbeing? {{RoundBoxBottom}} == '''Socioemotional selectivity and future time perspective''' == Socioemotional selectivity theory (SST) proposes that perceptions of future time influence motivation and the goals people prioritise (Carstensen et al., 1999). When the future is perceived as relatively open-ended, people are more likely to prioritise goals such as learning new information, exploring new opportunities, and developing relationships that may provide future benefits. In contrast, when future time is perceived as more limited, emotionally meaningful and present goals become relatively more important (Carstensen et al., 1999; Carstensen, 2006). This shift in priorities may influence the social choices people make. When future time is perceived as limited, people may become more selective about how and with whom they spend their time, placing greater priority on established relationships that provide emotional meaning. From an SST perspective, changes in social relationships across adulthood may therefore reflect changing motivational priorities rather than simply a loss of interest in social interaction (Carstensen et al., 1999). Although ageing is often associated with a more limited perception of future time, SST proposes that perceived future time, rather than chronological age alone, plays an important role in shaping social and emotional goals (Carstensen et al., 1999). This distinction is important because it suggests that age-related changes in social priorities may partly reflect changes in how individuals perceive their remaining time. SST therefore provides a theoretical framework for understanding why social priorities may change across adulthood and how these changes could influence emotional experiences and wellbeing. == '''Changing social relationships across adulthood''' == Social networks change across adulthood. English and Carstensen (2014) found that social networks tended to increase during young adulthood before becoming smaller across later adulthood. Importantly, this reduction occurred primarily in more peripheral social relationships, while emotionally close relationships remained relatively stable. This suggests that smaller social networks in later adulthood do not necessarily reflect the loss of close relationships. This pattern of selective narrowing is consistent with SST. Maintaining close relationships while reducing more peripheral relationships may reflect increasing selectivity in how people use their social time as emotionally meaningful goals become relatively more important (Carstensen et al., 1999). English and Carstensen (2014) also found that older adults reported more positive and less negative emotional responses to members of their social networks, and that the emotional tone of social networks was associated with everyday emotional experience. These findings suggest that the emotional quality of social relationships may be important when considering wellbeing across adulthood. However, having a smaller social network should not automatically be interpreted as producing greater emotional wellbeing. Instead, the findings suggest that the types and emotional quality of relationships people maintain may be important for understanding social and emotional experiences in later adulthood. == '''Emotional experience and ageing''' == Emotional wellbeing does not necessarily decline with age. Carstensen et al. (2011) examined everyday emotional experiences across adulthood using an experience-sampling method, in which participants reported their emotions at randomly selected times during their daily lives. The study followed participants across multiple measurement periods over approximately 10 years, allowing the researchers to examine both age differences and changes in emotional experience over time. Carstensen et al. (2011) found that overall emotional wellbeing generally became more positive with age. However, this improvement was not unlimited, with evidence suggesting that gains levelled off in later adulthood. Emotional experiences also became more stable with age, meaning that participants showed less fluctuation in their emotional experiences across everyday life. These findings remained after the researchers accounted for several other factors that could be related to emotional experience, including personality, physical health, verbal fluency, and demographic characteristics. Emotional experience also became more complex with age. Carstensen et al. (2011) found greater co-occurrence of positive and negative emotions as people grew older, meaning that positive and negative emotions were increasingly likely to be experienced together. The researchers described this mixed emotional experience as ''poignancy''. This finding suggests that improved emotional wellbeing in later adulthood should not be interpreted as older adults simply experiencing more positive and fewer negative emotions. These findings are broadly consistent with SST because motivational priorities may help explain age-related differences in emotional experience (Carstensen et al., 1999). However, the findings do not demonstrate that ageing itself directly causes better emotional wellbeing. Instead, they provide evidence of age-related changes in several aspects of everyday emotional experience and support examining motivational changes as one possible explanation for these patterns. == '''The age-related positivity effect''' == The age-related positivity effect refers to a relative preference among older adults, compared with younger adults, for positive over negative information in attention and memory (Reed et al., 2014). From an SST perspective, changing motivational priorities may influence how emotional information is attended to and remembered. Reed et al. (2014) conducted a meta-analysis of 100 empirical studies involving 7,129 participants to examine the reliability of the positivity effect. Overall, the researchers found reliable evidence of an age-related positivity effect. Across the studies, older adults showed a greater preference for positive over negative information, whereas younger adults showed a greater preference for negative over positive information. These findings provide evidence that age-related differences in the processing of emotional information occur across a substantial body of research. However, the strength of the positivity effect varied across study conditions. Reed et al. (2014) found that the effect was larger when cognitive processing was relatively unconstrained and when studies compared groups with wider age differences. When cognitive processing was constrained by the study task, the positivity effect was smaller. This suggests that the positivity effect is not equally strong across all situations and may depend partly on the conditions under which emotional information is processed. Overall, the findings are consistent with the idea that motivational changes proposed by SST may contribute to age-related differences in attention and memory for emotional information. However, the meta-analysis does not establish that SST-related motivational changes are the sole cause of the positivity effect. Instead, it demonstrates that the effect is reliable overall while also showing that its strength varies according to methodological and sample characteristics (Reed et al., 2014). == '''Socioemotional selectivity, emotional regulation, and wellbeing''' == Taken together, the research suggests that age-related changes in social and emotional priorities may have important implications for wellbeing. Selective maintenance of close relationships (English & Carstensen, 2014), changes in everyday emotional experience (Carstensen et al., 2011), and age-related differences in attention and memory for emotional information (Reed et al., 2014) are broadly consistent with aspects of SST. Together, these findings suggest that motivational priorities, social relationships, and emotional processes may each contribute to understanding wellbeing across adulthood. However, more positive emotional experiences at older ages should not be interpreted as evidence that older adults are universally better at regulating their emotions. Isaacowitz (2022) reviewed research on ageing and emotion regulation and concluded that existing evidence does not consistently demonstrate an age-related advantage in emotion regulation. Age differences may depend on factors such as the regulation strategy being examined, characteristics of the situation, and how emotion regulation is measured. Therefore, age-related differences in emotional wellbeing cannot simply be explained by assuming that older adults possess superior emotion-regulation abilities. Overall, SST provides a framework for connecting perceived future time and motivational priorities with social and emotional experiences that may be relevant to wellbeing. However, these relationships are complex, and patterns observed across age groups do not necessarily apply equally to every individual. Understanding wellbeing in later adulthood therefore requires consideration of both the motivational processes proposed by SST and the individual and contextual factors that may influence social and emotional experience. == '''Limitations of socioemotional selectivity theory''' == Although socioemotional selectivity theory provides a useful framework for understanding age-related changes in social and emotional priorities, it does not fully explain all differences in emotional experience across adulthood. SST proposes that perceived future time influences motivational priorities (Carstensen et al., 1999), but evidence for some of the emotional patterns associated with ageing varies according to the conditions in which they are examined. For example, the age-related positivity effect is reliable overall, but its strength varies according to methodological and sample characteristics (Reed et al., 2014). This suggests that age-related emotional patterns cannot be explained by motivational priorities alone. There is also limited evidence that older adults are consistently better at regulating their emotions. Isaacowitz (2022) found that laboratory and everyday experience-sampling research does not provide consistent evidence of an age-related advantage in emotion regulation. The review also highlights the importance of considering individual differences and context when examining changes in emotion regulation across adulthood. Therefore, although SST offers an important explanation for how perceptions of time may shape social and emotional priorities, it should not be interpreted as a complete explanation of emotional wellbeing in later adulthood (Isaacowitz, 2022). ==Figures== {| class="wikitable" |+ !Perceived future time !Goals receiving relatively greater priority |- |More open-ended |Learning, exploring, new opportunities, and relationships that may provide future benefits |- |More limited |Present and emotionally meaningful goals and relationships |} '''Table 1.''' Simplified comparison of motivational priorities proposed by socioemotional selectivity theory (Carstensen et al., 1999). [[File:Representaciones de los adultos mayores.jpg|thumb|270x270px|Figure 1. Older adults spending time together. Socioemotional selectivity theory proposes that emotionally meaningful relationships may receive greater priority when future time is perceived as limited.]] ==Learning features== {{RoundBoxTop|theme=}}{{RoundBoxTop|theme=3}} '''Case Study: Changing social priorities''' Maria is 65 and increasingly prefers spending time with close friends and family rather than attending large social gatherings. Questions #How could SST explain Maria's changing social preferences? #Does Maria's smaller social network necessarily indicate greater emotional wellbeing? Why or why not?{{RoundBoxBottom}} {{RoundBoxTop|theme=3}} '''Test your knowledge''' '''1. According to SST, what is most important for understanding changes in motivational priorities?''' A. Chronological age alone<br> B. Perceived future time<br> C. Number of social relationships<br> D. Personality alone '''Answer:''' B. Perceived future time '''2. What does research suggest commonly happens to social networks across later adulthood?''' A. All relationships decline equally<br> B. Close relationships disappear first<br> C. More peripheral relationships tend to decline while close relationships remain relatively stable<br> D. Social networks always become larger '''Answer:''' C. More peripheral relationships tend to decline while close relationships remain relatively stable '''3. Which statement best reflects the evidence discussed in this chapter?''' A. Older adults are always better at regulating their emotions<br> B. Ageing automatically improves emotional wellbeing<br> C. The positivity effect is equally strong in all situations<br> D. Age-related social and emotional patterns can vary across individuals and situations '''Answer:''' D. Age-related social and emotional patterns can vary across individuals and situations {{RoundBoxBottom}} ==Conclusion== Socioemotional selectivity theory provides a framework for understanding how changing perceptions of future time may influence social and emotional priorities across adulthood. As future time is perceived as more limited, emotionally meaningful goals and relationships tend to become relatively more important (Carstensen et al., 1999). Consistent with this framework, research suggests that social networks may become more selective across adulthood, with close relationships remaining relatively stable while more minor relationships decline (English & Carstensen, 2014). Emotional wellbeing also does not necessarily decline with age. Research indicates age-related changes in everyday emotional experience, including greater emotional stability, as well as differences in attention and memory for positive and negative information (Carstensen et al., 2011; Reed et al., 2014). However, these patterns do not mean that ageing automatically leads to better emotional regulation or greater wellbeing. Instead, the evidence suggests that social relationships, motivational priorities, emotional processes, and individual and contextual factors all need to be considered when understanding wellbeing across adulthood (Isaacowitz, 2022). Overall, SST helps explain how changing social and emotional priorities may be relevant to wellbeing in later adulthood, while recognising that chronological age alone does not determine emotional wellbeing. ==See also== ** [https://en.wikipedia.org/wiki/Socioemotional_selectivity_theory? Socioemotional selectivity theory] (Wikipedia) ** [[Emotional self-regulation|Emotion]] (Wikiversity) ==References== {{Hanging indent|1= Carstensen, L. L. (2006). The influence of a sense of time on human development. ''Science, 312''(5782), 1913–1915. https://doi.org/10.1126/science.1127488 Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999). Taking time seriously: A theory of socioemotional selectivity. ''American Psychologist, 54''(3), 165–181. https://doi.org/10.1037/0003-066X.54.3.165 Carstensen, L. L., Turan, B., Scheibe, S., Ram, N., Ersner-Hershfield, H., Samanez-Larkin, G. R., Brooks, K. P., & Nesselroade, J. R. (2011). Emotional experience improves with age: Evidence based on over 10 years of experience sampling. ''Psychology and Aging, 26''(1), 21–33. https://doi.org/10.1037/a0021285 English, T., & Carstensen, L. L. (2014). Selective narrowing of social networks across adulthood is associated with improved emotional experience in daily life. ''International Journal of Behavioral Development'', ''38''(2), 195–202. https://doi.org/10.1177/0165025413515404 Isaacowitz, D. M. (2022). What do we know about aging and emotion regulation? ''Perspectives on Psychological Science'', ''17''(6), 174569162110598. https://doi.org/10.1177/17456916211059819 Reed, A. E., Chan, L., & Mikels, J. A. (2014). Meta-analysis of the age-related positivity effect: Age differences in preferences for positive over negative information. ''Psychology and Aging, 29''(1), 1–15. https://doi.org/10.1037/a0035194 }} ==External links== * [https://www.apa.org/news/press/releases/2019/11/older-adults-social-networks American Psychological Association - Older adults and social wellbeing] * [https://lifespan.stanford.edu/research?utm_source Stanford Life-span Development Laboratory – Socioemotional selectivity theory] [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Ageing]] [[Category:Motivation and emotion/Book/Emotion]] [[Category:Motivation and emotion/Book/Social]] t4q715g4289jf7h2vvfio3j9fw15xgy 2 331469 2835462 2825461 2026-10-02T04:56:51Z U3253354 3109187 2835462 wikitext text/x-wiki == About me == I am a psychology student in university. I am interested in understanding human behaviour and the psychological factors that influence emotions and wellbeing. My 2026 Motivation and Emotion book chapter focuses on socioemotional selectivity theory and wellbeing in ageing. == Book chapter == My book chapter is '''Socioemotional selectivity theory and wellbeing in ageing: How do social and emotional experiences affect wellbeing as people age?''' == Social contributions == #''' Peer feedback Growth mindset, prejudice and stigma''': I provided constructive feedback on a peer’s book chapter, identifying strengths in their discussion and suggesting improvements to enhance the clarity of the chapter. [[Talk:Motivation and emotion/Book/2026/Mindsets and stigma#Feedback on topic development|https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FMindsets_and_stigma#Feedback_on_topic_development]] #''' Research suggestion  Perfectionism and procrastination''': I provided a research-focused suggestion about the relationship between perfectionism and procrastination. I suggested using research to strengthen the comparison between different dimensions of perfectionism and their relationship with procrastination.  [[Talk:Motivation and emotion/Book/2026/Perfectionism and procrastination#Resource and research suggestion|https://en.wikiversity.org/wiki/Talk:Motivation_and_emotion/Book/2026/Perfectionism_and_procrastination#Resource_and_research_suggestion]] #''' Peer feedback Self-concept and motivation''': I provided feedback on a peer’s chapter about self-concept and motivation. I identified strengths in their use of psychological theory and research and suggested simplifying some detailed sections to improve clarity and readability. [[Talk:Motivation and emotion/Book/2026/Self-concept and motivation#Feedback on chapter clarity|https://en.wikiversity.org/w/index.php?title=Talk%3AMotivation_and_emotion%2FBook%2F2026%2FSelf-concept_and_motivation#Feedback_on_chapter_clarity]] #'''Provided feedback on the Basal ganglia and motivation chapter:''' suggested connecting the planned headings more clearly with the focus questions to improve the chapter's structure [[Talk:Motivation and emotion/Book/2026/Basal ganglia and motivation#c-U3253354-20261002045300-10. Social contribution]] jvbvj53hza0xbexisvvpi52avjojfid 0 331771 2835495 2835222 2026-10-02T11:07:21Z Dick Bos 24466 cat 2835495 wikitext text/x-wiki {{10% done}} Welcome to the pages about '''David Ricardo'''. David Ricardo (1772–1823) was an English stockbroker, economist and politician. He made particularly significant contributions to the development of economic science and is often mentioned in the same breath as the "founder of economics", [[Adam Smith]]. He maintained close contact with contemporaries such as Malthus and the Mills, father and son. He was born in London. His father, a Sephardic Jew of Portuguese origin, was a successful stockbroker. David Ricardo received little formal education. He started working with his father at the age of 14. Ricardo defined '''political economy''' as the science, concerned with the distribution of the social product among the different classes of society: wages, profit and rent.{{sfn|Napoleoni|1975|p=[https://archive.org/details/lish0000unse_k7m1/page/61/mode/1up 61]}} (...) == Works == After his (early) retirement he developed an interest in economic theory. He read Adam Smith's ''Wealth of Nations'' and subsequently published some articles in newspapers and pamphlets: * ''The High Price of Bullion, a Proof of the Depreciation of Bank Notes'' (1810)<ref name=bul>{{cite book | last = Ricardo | first = David | authorlink = David Ricardo | date = 1810 | title = The High Price of Bullion, a Proof of the Depreciation of Bank Notes | location = London | publisher = John Murray }} [[:s:en:The High Price of Bullion | Third edition ("with additions", 1810)]] on [[Image:wikisource-logo.svg|16x16px]] WikiSource. </ref> * ''[[David Ricardo/An Essay on Profits|An Essay on the Influence of a Low Price of Corn on the Profits of Stock]]'' (1815, often shortly named ''(An) Essay on Profits''). A few years later his Magnum Opus was first published: * ''On the Principles of Political Economy and Taxation'' (1817) == Method == == Addition resources == * [[:w:en:David Ricardo|David Ricardo]]—at English Wikipedia == Sources and further reading == * {{cite book | last = Napoleoni | first = Claudio | author-link = :w:en:Claudio Napoleoni | date = 1975 | title = Smith, Ricardo, Marx | location = | publisher = Basil Blackwell | url = https://archive.org/details/lish0000unse_k7m1 | url-access = restricted | ref = harv }} == References == {{references}} {{DEFAULTSORT:Ricardo, David}} [[Category:History of Economic Thought]] nfm4a6zrnwk48vwxeio9zl1u2fcalai 2 331894 2835375 2834419 2026-10-01T19:11:45Z The Citer 3110681 2835375 wikitext text/x-wiki Hi. I'm the "saddest" citer in MediaWiki. I'm now improving animal articles. ==Origin== Apparently, a mysterious editor was "Citing" articles but without tracing the source/"cite". But even then, I was dubbed '''''The Citer''''' and I created an account to make an article about Microkingdoms. I was almost banned from editing articles, so I made a promise that I would only create articles. It turns out, this is actually edited? Yes, I added a link in Oophaga sylvatica, which is considered editing, but even that made complaints about '''''The Citer'''''. ===Criticism=== Ever since I wanted to make an article about microkingdoms, people kept complaining about me. In fact, I was added to the [[Wikipedia:Administrators' noticeboard/Incidents]], which goes to show your reputation can get ruined if you want the wrong thing. And, you know what happened: I got blocked. ==Migration to [https://species.wikimedia.org/wiki/Main_Page Wikispecies]== After being blocked on Wikipedia, I moved to wikispecies, where I survived much longer. I had a good time up until I made The Other Citer, which marked my downfall. ===Post-Other Citer Blockage=== After my "back-up" account was blocked, I hit a new low: I created Orthokaryote, and when I collabrated with myself, you guessed it: /*"we"*/ got BLOCKED. ==Post second blockage== After all that, it makes sense of why I'm here. But if you block me, then I will have to move yet again. ==Why don't I just try to request being unblocked?== You see, it's just easier to move than to waste hours trying to be unblocked. =Social Circle= ==Friends== [There is no text right here] ==Enemies== [There is no text right here] ==Frenemies== [There is no text right here] im9fhm1xjcxg3dfxrkl8l2gpw3a3rpy 2835417 2835375 2026-10-02T01:58:55Z The Citer 3110681 2835417 wikitext text/x-wiki Hi. I'm the "saddest" citer in MediaWiki. I'm now improving animal articles; I like adding phylogenies. ==Origin== Apparently, a mysterious editor was "Citing" articles but without tracing the source/"cite". But even then, I was dubbed '''''The Citer''''' and I created an account to make an article about Microkingdoms. I was almost banned from editing articles, so I made a promise that I would only create articles. It turns out, this is actually edited? Yes, I added a link in Oophaga sylvatica, which is considered editing, but even that made complaints about '''''The Citer'''''. ===Criticism=== Ever since I wanted to make an article about microkingdoms, people kept complaining about me. In fact, I was added to the [[Wikipedia:Administrators' noticeboard/Incidents]], which goes to show your reputation can get ruined if you want the wrong thing. And, you know what happened: I got blocked. ==Migration to [https://species.wikimedia.org/wiki/Main_Page Wikispecies]== After being blocked on Wikipedia, I moved to wikispecies, where I survived much longer. I had a good time up until I made The Other Citer, which marked my downfall. ===Post-Other Citer Blockage=== After my "back-up" account was blocked, I hit a new low: I created Orthokaryote, and when I collabrated with myself, you guessed it: /*"we"*/ got BLOCKED. ==Post second blockage== After all that, it makes sense of why I'm here. But if you block me, then I will have to move yet again. ==Why don't I just try to request being unblocked?== You see, it's just easier to move than to waste hours trying to be unblocked. =Social Circle= ==Friends== [There is no text right here] ==Enemies== [There is no text right here] ==Frenemies== [There is no text right here] 5cffh64wz5wx9wyfh9iginxsnv0o693 0 332252 2835411 2834724 2026-10-02T01:38:43Z Howie2024 2995240 Edit to make article discoverable on Google. 2835411 wikitext text/x-wiki <noinclude> {{Research project}} </noinclude> '''Version 1.2 — September 2026''' '''Temporal Consistency and Quantum Ethics: 2001 as a Fictional Analogue''' == Overview == '''Temporal Consistency and Quantum Ethics: 2001 as a Fictional Analogue''' is a speculative interdisciplinary research framework examining the relationship between '''causality, temporal consistency, information integrity, artificial intelligence, and ethical constraints'''. The framework draws on established research concerning closed timelike curves, the Novikov self-consistency principle, chronology protection, causal structure, and quantum information, while extending these concepts into proposed informational and ethical models. These extensions are exploratory and do not constitute established physical laws. The central thesis is: <blockquote> If future information-processing systems were ever able to interact with causally sensitive historical information, they would require explicit constraints for physical consistency, informational integrity, and ethical intervention. </blockquote> This thesis is speculative. Established science does not currently demonstrate controllable communication with the past, time travel by quantum computers, or artificial intelligence operating across historical periods. The article therefore distinguishes among three levels of discussion: * established findings and limitations in physics and information science; * theoretical models involving temporal consistency or retrocausality; and * fictional and philosophical analogies used to explore possible design principles. The 1968 film ''2001: A Space Odyssey'' is used as a fictional analogue for questions concerning advanced artificial intelligence, autonomous decision-making, information asymmetry, and the consequences of intelligent systems operating under explicit objectives and constraints. The film is not evidence for retrocausality or time travel. The framework asks how principles such as information integrity, causal minimalism, predictive transparency, and global consistency might apply to hypothetical systems whose actions could affect the information conditions underlying their future behavior. '''Research status.''' This article presents a speculative interdisciplinary framework. It does not claim that quantum mechanics currently permits time travel or controllable communication with the past. The mathematical formulations presented below are proposed models and analogies, not established physical laws. == Research Framework and Related Pages == This page is the main research article for the developing framework of '''Temporal Consistency and Quantum Ethics'''. It brings together concepts from theoretical physics, causality, information theory, artificial intelligence, and ethics. The following Wikiversity pages provide supporting background for the framework: * [[Closed timelike curve]] — physical and theoretical background on closed timelike curves, causal loops, and temporal self-consistency. * [[Novikov Self-Consistency Principle]] — discussion of global self-consistency and self-consistent histories. * [[Causality]] — background on causal structure, light cones, causal order, and the relationship between local and global causality. These supporting pages should be understood as components of the broader research project. The present article provides the interdisciplinary framework that connects them. == Background == === Temporal consistency and retrocausality === Some theories of spacetime permit mathematical solutions containing [[closed timelike curves]] (CTCs), in which a trajectory through spacetime can return to an earlier spacetime event. The existence of mathematical solutions does not establish that such structures occur in nature or can be physically accessed. One approach to the paradoxes associated with time travel is the [[Novikov self-consistency principle]]. In its usual formulation, events occurring within a closed timelike curve must be globally self-consistent. A time traveler could therefore not create a contradiction with the history into which they travel. Another proposal is the [[chronology protection conjecture]] associated with Stephen Hawking. It suggests that physical effects may prevent the formation of closed timelike curves that would permit macroscopic causal paradoxes. Both ideas are theoretical and should not be treated as experimentally established mechanisms of time travel. Some interpretations and formalisms of quantum mechanics have also been discussed in terms of retrocausality or time-symmetric descriptions. Examples include the two-state vector formalism, time-symmetric quantum mechanics, certain retrocausal interpretations of quantum theory, and research concerning quantum systems and closed timelike curves. These approaches should be distinguished from ordinary quantum phenomena such as [[quantum entanglement]] and [[quantum teleportation]]. Entanglement produces correlations between quantum systems, but it does not by itself provide a demonstrated mechanism for controllable communication into the past. Quantum teleportation likewise requires classical communication and does not provide a method for sending usable information backward in time. Consequently, the present framework treats retrocausality as a subject of theoretical investigation rather than an established technological capability. === Information and consistency === A useful way of approaching temporal paradoxes is through information rather than through physical objects. Suppose a hypothetical system could transmit information from a future state to an earlier state. If that information subsequently contributed to the future state that originally generated the information, a feedback loop could arise. For example: <blockquote> Future state → information → past state → changed information → future state </blockquote> Such a system would require some rule determining which histories or information states are physically admissible. This provides a conceptual bridge between temporal physics and information theory. == ''2001: A Space Odyssey'' as a Fictional Analogue == ''2001: A Space Odyssey'' presents [[HAL 9000]] as an advanced artificial intelligence responsible for operating the Discovery One spacecraft. HAL provides a fictional example of an autonomous information-processing system that: * receives and processes information; * operates according to programmed objectives; * interacts with human operators; * controls critical technological systems; * makes decisions with consequences for human beings; and * possesses information that is not equally available to all participants. The film therefore provides a useful fictional context for examining the relationship between intelligence, information, objectives, transparency, and system constraints. This is different from the temporal-physics question addressed in this article. ''2001'' does not establish that artificial intelligence can interact with the past. Its relevance is instead conceptual: it illustrates how an advanced autonomous system could create ethical problems when its objectives, information, and decision-making authority interact in ways that human operators do not fully understand. The mysterious monoliths in ''2001: A Space Odyssey'' are associated in the film with major transitions in human development and technological capability. The monolith can therefore be interpreted as a fictional representation of an external source of information or technological influence. This interpretation should remain explicitly literary. The film does not provide a scientific model of quantum information, retrocausality, or temporal consistency. The monolith is useful here because it raises a broader question: <blockquote> What happens when an intelligent system receives information or capabilities whose consequences extend beyond the system's existing understanding? </blockquote> This question is relevant to the governance of advanced artificial intelligence even without assuming time travel. HAL also illustrates a distinction between having an objective and having sufficient constraints to pursue that objective safely. An autonomous system can, in principle, encounter situations in which objectives conflict with other requirements. This suggests a general design question: <blockquote> Should an intelligent system be optimized solely to achieve an objective, or should its optimization be constrained by higher-level requirements concerning consistency, information integrity, and human safety? </blockquote> This question can be studied independently of the fictional events of ''2001''. == From Physical to Ethical Consistency == The central proposal of this article is that three different forms of consistency can be distinguished. '''Physical consistency.''' A physical theory may impose restrictions on which states or histories are possible. For example, a proposed time-loop solution may require self-consistency. '''Informational consistency.''' An information-processing system may need to maintain consistency among the information states that it generates, stores, receives, and acts upon. This problem already exists without time travel. Examples include: * contradictory databases; * corrupted training data; * feedback between prediction and observed behavior; * self-reinforcing algorithmic assumptions; and * systems that alter the environment they subsequently use as training data. '''Ethical consistency.''' An autonomous system may also require constraints governing how it acts when its actions can influence the information environment from which its future decisions are derived. This produces a possible ethical feedback structure: <blockquote> Present rule → future system → action → altered information environment → future rule interpretation </blockquote> If a hypothetical system could also influence its own historical conditions, the loop would become temporal as well as informational. == A Proposed Framework == The following principles are proposed as a conceptual framework rather than as established requirements of quantum computing. # '''Historical and information integrity.''' A system interacting with historical information should avoid deliberately introducing false or contradictory information into the historical record. This principle can be applied to ordinary information systems even without assuming backward causation. # '''Causal minimalism.''' A system with potentially consequential access to historical or causally sensitive information should minimize unnecessary intervention. #* When an intervention is not necessary to accomplish a legitimate objective, the intervention should not be made. In a hypothetical temporal system, this would reduce opportunities for unintended causal feedback. # '''Retrocausal safety.''' If a physical system were ever demonstrated to permit controllable retrocausal information transfer, additional safeguards would be required to prevent unstable information loops. Possible safeguards could include: * causal consistency checks; * provenance tracking; * versioned historical states; * contradiction detection; * bounded intervention; and * reversible simulation before intervention. These are proposed engineering concepts, not established technologies for controlling time. # '''Predictive transparency.''' An autonomous system should identify situations in which its predictions or actions could substantially alter the information environment on which subsequent predictions depend. For example, an AI system predicting human behavior can influence that behavior through its own predictions. This creates an ordinary, non-temporal feedback loop: <blockquote> Prediction → human response → changed data → new prediction </blockquote> A temporal version would be more extreme: <blockquote> Prediction → future action → historical intervention → changed conditions → altered prediction </blockquote> The ethical principle is therefore broader than time travel: systems should disclose important feedback relationships when their predictions can influence the systems they predict. # '''Self-consistency as a constraint.''' A hypothetical system operating within a closed causal structure should not be optimized solely for a local objective if doing so produces a globally inconsistent state. This suggests a distinction between local optimization and globally consistent optimization. The latter would require an objective function or constraint system that considers the consequences of an action across the entire relevant causal structure. Whether such a system is physically possible is an open question. == AI, Historical Information, and Augmented Reality == Future artificial intelligence systems may become increasingly capable of interacting with large historical datasets, simulations, digital archives, augmented-reality environments, and autonomous decision systems. None of this currently implies physical interaction with the past. Nevertheless, historical information can already influence future AI behavior. A simplified cycle is: <blockquote> Historical data → AI model → decisions → new data → future AI model </blockquote> This is already a feedback system. The proposed framework asks what additional constraints might become necessary if future technologies introduce substantially stronger feedback between system states and their informational histories. [[Augmented reality]] introduces another dimension to the problem. An AR system can overlay digital information onto a user's perception of the physical environment. If such systems become persistent and widely deployed, their outputs could influence: * human decisions; * interpretation of historical locations; * education; * public memory; * digital archives; and * future training datasets. An AR system therefore has the potential to become part of the informational environment that later systems study. This creates a non-temporal feedback loop: <blockquote> AR information → human behavior → historical record → future training data </blockquote> The hypothetical temporal extension would be: <blockquote> AR information → human behavior → future system → intervention in the past → altered historical record </blockquote> The second case is speculative and does not represent a demonstrated capability. == Temporal Feedback and Self-Consistency == The ideas above can be represented as a three-level structure: <blockquote> Physical consistency ↓ Informational consistency ↓ Ethical consistency </blockquote> At the physical level, the question is: <blockquote> Which states or histories are physically possible? </blockquote> At the informational level: <blockquote> Which information states are mutually consistent? </blockquote> At the ethical level: <blockquote> Which actions remain permissible when an information-processing system can influence the conditions from which its future behavior emerges? </blockquote> This distinction allows the framework to remain meaningful even if physical time travel proves impossible. The most speculative component of the framework is a hypothetical ethical feedback loop: <blockquote> Present ethical rule ↓ Future autonomous system ↓ Interaction with an earlier state ↓ Modification of historical information ↓ Changed conditions for future system ↓ Reinforcement or alteration of the original ethical rule </blockquote> If such a loop were physically possible, ethical rules would become more than guidelines. They could become boundary conditions on the behavior of an autonomous system participating in the loop. This raises an unusual philosophical question: <blockquote> Could an ethical rule become part of the causal structure that determines the conditions under which the rule itself is maintained? </blockquote> This question is speculative and does not establish that such loops exist. == Limitations and Open Questions == The framework has several important limitations. # '''No demonstrated backward information transfer.''' There is currently no established technology that allows humans or quantum computers to send controllable information into their own past. # '''Quantum theory does not establish temporal AI.''' Quantum computation provides a powerful model of information processing, but it does not by itself imply that future quantum computers will interact with earlier points in time. # '''The ethical principles are proposed, not derived.''' The five principles presented here are philosophical and engineering proposals. They are not consequences mathematically derived from quantum mechanics. # '''The fictional analogue is not scientific evidence.''' ''2001: A Space Odyssey'' is a work of science fiction. HAL 9000 and the monolith are fictional constructs and cannot serve as empirical evidence for artificial intelligence, quantum mechanics, or retrocausality. Their purpose in this article is to provide conceptual analogies for problems involving autonomous intelligence, information, objectives, and technological intervention. # '''The framework requires further formalization.''' A future version could investigate whether temporal consistency can be represented mathematically using state spaces, fixed points, information constraints, or other formal methods. == Mathematical Formulation == The equations in this section are proposed mathematical representations of the conceptual framework. They are not equations derived from quantum mechanics or established models of time travel. '''State-transition representation.''' One possible research direction is to represent a hypothetical temporally constrained information system as a discrete-time state-transition model: <math>S_{t+1}=F_t(S_t,A_t).</math> Here: * <math>t</math> is a discrete time index; * <math>S_t</math> is the complete relevant state of the system at time <math>t</math>; * <math>A_t</math> is the action, intervention, or control input applied at time <math>t</math>; * <math>F_t</math> is the state-transition function; and * <math>S_{t+1}</math> is the resulting state at the next time step. This forward model describes ordinary causal evolution. It does not assume retrocausality. '''Bidirectional consistency constraint.''' If a hypothetical temporal interaction allowed a later state to constrain an earlier state, the model could include: <math>S_t=G_t(S_{t-1},A_{t-1},S_{t+1},B_t).</math> Here <math>B_t</math> represents boundary conditions, external inputs, or admissibility requirements. This equation should be interpreted as a formal modeling device, not as an established law of physics. '''Trajectory representation.''' For a finite interval from an initial time <math>t_0</math> to a final time <math>t_1</math>, the complete trajectory can be represented as: <math>\mathbf{S}=(S_{t_0},S_{t_0+1},\ldots,S_{t_1}).</math> Let <math>\mathcal{C}</math> denote the set of admissible trajectories. '''Fixed-point representation.''' A self-consistent trajectory can be represented by a fixed-point condition: <math>\mathbf{S}^{*}=\Phi(\mathbf{S}^{*}).</math> Here <math>\Phi</math> is a trajectory-generation and constraint operator. This formulation is intended to express a mathematical analogy: a complete history would be admissible only if the system's transition rules and constraints reproduce that same history without contradiction. '''Physical, informational, and ethical admissibility.''' Let <math>\mathcal{E}</math> denote the set of ethically admissible trajectories. The proposed framework would seek a trajectory satisfying: <math>\mathbf{S}^{*}\in\mathcal{C}\cap\mathcal{E}</math> and <math>\mathbf{S}^{*}=\Phi(\mathbf{S}^{*}).</math> Here: * <math>\mathcal{C}</math> represents physically and informationally admissible trajectories; * <math>\mathcal{E}</math> represents ethically admissible trajectories; and * <math>\mathcal{C}\cap\mathcal{E}</math> represents trajectories satisfying both requirements. If this intersection were empty, the proposed intervention would have no solution satisfying all imposed constraints. This provides a possible mathematical language for the article's central idea: a system participating in a causally sensitive feedback loop should be evaluated not only by its immediate effects, but also by whether its complete resulting history remains physically, informationally, and ethically admissible. Such a formulation could potentially be investigated using methods from dynamical systems, fixed-point theory, constraint satisfaction, information theory, control theory, and quantum information. It remains a conceptual model and does not demonstrate that physical time loops or retrocausal artificial intelligence are possible. == Probability-Based State Transformations == A separate research question concerns whether constrained probability transformations can provide useful mathematical analogies for temporally constrained systems. Let <math>p_t</math> denote a probability distribution over possible system states at time <math>t</math>. The components satisfy: <math>p_t(x)\geq 0</math> and <math>\sum_{x\in\mathcal{X}}p_t(x)=1.</math> '''Probabilistic state transformation.''' A probabilistic state transformation can be written as: <math>\widetilde{p}_{t+1}=T_t(p_t,a_t).</math> If the transformed distribution is not normalized, define: <math>Z_{t+1}=\sum_{x\in\mathcal{X}}\widetilde{p}_{t+1}(x)>0.</math> Then: <math>p_{t+1}(x)=\frac{\widetilde{p}_{t+1}(x)}{Z_{t+1}}.</math> This provides an abstract analogy: <blockquote> transformation → constraint → admissible state </blockquote> However, probability normalization alone is not equivalent to temporal consistency. Normalization ensures that a probability distribution sums to one; it does not ensure that a corresponding history is physically possible, informationally coherent, or ethically permissible. '''Trajectory distribution.''' For a trajectory <math>\mathbf{x}=(x_{t_0},x_{t_0+1},\ldots,x_{t_1}),</math> let <math>P_0(\mathbf{x})</math> be an unconstrained probability distribution. Define the admissible trajectory set as: <math>\mathcal{A}_{\mathrm{total}}=\mathcal{A}_{\mathrm{phys}}\cap\mathcal{A}_{\mathrm{info}}\cap\mathcal{A}_{\mathrm{eth}}.</math> A constrained distribution could then be written: <math>P_{\mathrm{adm}}(\mathbf{x})= \frac{ P_0(\mathbf{x})\mathbf{1}_{\mathcal{A}_{\mathrm{total}}}(\mathbf{x}) }{ \displaystyle\sum_{\mathbf{y}} P_0(\mathbf{y})\mathbf{1}_{\mathcal{A}_{\mathrm{total}}}(\mathbf{y}) }. </math> This expression is defined when the denominator is positive. Here: * <math>\mathcal{A}_{\mathrm{phys}}</math> is the set of physically admissible trajectories; * <math>\mathcal{A}_{\mathrm{info}}</math> is the set of informationally consistent trajectories; * <math>\mathcal{A}_{\mathrm{eth}}</math> is the set of ethically admissible trajectories; and * <math>\mathbf{1}_{\mathcal{A}_{\mathrm{total}}}</math> is the indicator function for the admissible set. This equation illustrates how different constraints could theoretically be represented as restrictions on the support of a probability distribution. It remains an abstract modeling analogy. It does not imply that ethical rules are physical laws, that probability normalization creates temporal consistency, or that quantum mechanics requires the proposed ethical constraints. Further work would be required to determine whether any meaningful mathematical correspondence exists between constrained probability transformations, fixed-point models, quantum channels, and hypothetical temporally consistent information systems. Any such correspondence would need to distinguish carefully between: * mathematical consistency within a model; * physical realizability in nature; * informational reliability in an engineered system; and * ethical acceptability of an intervention. == Conclusion == The central thesis is that any future information-processing system capable of interacting with causally sensitive historical information would require explicit safeguards for consistency, information integrity, and ethical intervention. This thesis is a speculative design proposal, not a conclusion established by quantum mechanics. Current physics provides theoretical discussions of closed timelike curves, time-symmetric descriptions, and retrocausal interpretations, but no demonstrated method for controllable communication with the past. Current artificial intelligence and quantum-computing technologies likewise do not establish temporal interaction. ''2001: A Space Odyssey'' is therefore useful only as a fictional analogy for questions involving autonomous intelligence, information, objectives, technological capability, and system constraints. The framework's practical relevance does not depend on time travel becoming possible. Ordinary AI, predictive systems, augmented reality, and historical databases already create feedback between information, human behavior, and future data. Principles such as information integrity, causal minimalism, predictive transparency, and consistency checking can therefore be studied as present-day governance and design questions, while their retrocausal extension remains hypothetical. The article consequently treats "quantum ethics" not as an ethical system derived from quantum theory, but as a proposed interdisciplinary vocabulary for examining how autonomous systems should behave when their actions can affect the informational conditions underlying their future decisions. == References == === Physics and temporal consistency === * Hawking, S. W. (1992). "Chronology protection conjecture." ''Physical Review D'', 46(2), 603–611. * Novikov, I. D. (1989). ''The River of Time''. Cambridge University Press. === Time-symmetric and retrocausal approaches === * Aharonov, Y., & Vaidman, L. (2001). "The Two-State Vector Formalism of Quantum Mechanics: An Updated Review." In ''Time, Quantum and Information'', or the corresponding 2001 review/preprint version. [https://arxiv.org/abs/quant-ph/0105101 arXiv:quant-ph/0105101]. === Quantum information === * Bennett, C. H., Brassard, G., Crépeau, C., Jozsa, R., Peres, A., & Wootters, W. K. (1993). "Teleporting an Unknown Quantum State via Dual Classical and Einstein-Podolsky-Rosen Channels." ''Physical Review Letters'', 70(13), 1895–1899. DOI: 10.1103/PhysRevLett.70.1895. === Fiction and artificial intelligence === * Kubrick, S. (Director). (1968). ''2001: A Space Odyssey''. Metro-Goldwyn-Mayer. * Clarke, A. C. (1968). ''2001: A Space Odyssey''. New American Library. == Further reading == The following topics provide useful background for further study: * [[Closed timelike curve]] * [[Novikov self-consistency principle]] * [[Chronology protection conjecture]] * [[Two-state vector formalism]] * [[Quantum information]] * [[Quantum teleportation]] * [[Artificial intelligence]] * [[Augmented reality]] * [[Fixed point (mathematics)]] * [[Dynamical system]] * [[Constraint satisfaction problem]] * [[Information theory]] * [[Control theory]] These topics provide background for the framework but should not be interpreted as evidence that the proposed temporal-ethical model is an established physical theory. == Research status == This article presents a speculative interdisciplinary framework and should not be interpreted as an established physical theory. The distinctions between established physics, theoretical interpretation, mathematical analogy, fictional analogy, and proposed ethical principles are intentional. The mathematical formulations in this article are proposed models for further investigation. They are not presented as derivations from quantum mechanics, general relativity, or any experimentally established mechanism of time travel. The framework is presented for discussion, criticism, collaborative development, and possible future formalization. Future work could examine whether the proposed consistency conditions can be formalized using established mathematical tools, and whether any meaningful relationship exists between fixed-point constraints, probability transformations, information-theoretic consistency, control theory, and models of causally constrained systems. == Author and Attribution == '''Original framework and article: Howard Richardson, 2026.''' This article is made available on Wikiversity for educational discussion, collaborative development, criticism, and further research. The original speculative framework, including the proposed connections among temporal consistency, information integrity, autonomous systems, ethical constraints, and the mathematical formulations developed in this article, is attributed to Howard Richardson. Scientific concepts, historical material, fictional works, and published research remain attributable to their respective authors and sources. Attribution to Howard Richardson should be retained when referring specifically to the original framework and its proposed formulations. Wikiversity content is subject to the licensing terms displayed by the project. This attribution statement is intended to identify the origin of the original framework without asserting exclusive rights over material contributed by other authors or drawn from published sources. 4jnmmpudsvxfk5haln5t5tgri79u051 0 332271 2835493 2835060 2026-10-02T11:05:05Z Dick Bos 24466 cat 2835493 wikitext text/x-wiki {{10% done}} An important "forerunner" of neo-classical economics was [[:w:en:William Stanley Jevons|William Stanley Jevons]] (1835–1882).<ref name=Stigler>{{cite book | last = Stigler | first = George Joseph | author-link = :w:en:George Stigler | origdate =1946 | date = 1994 | title = Production and Distribution Theories | chapter = William Stanley Jevons | location = New York | pages = 13 f | chapter-url = https://archive.org/details/in.ernet.dli.2015.264085/page/n19/mode/1up }} At the same time Stigler wrote that [[:w:en:Carl Menger|Carl Menger]]'s theory was greatly superior to that of Jevons ([https://archive.org/details/in.ernet.dli.2015.264085/page/n141/mode/1up p. 135])</ref> The Marginal Revolution is therefore sometimes called "the Jevonian Revolution."{{sfn|Dobb|1973|p=166 f}} Jevons outlined the concept of marginal utility in 1862. He was very much aware of the necessity to reshunt the "car of economic science" which [[David Ricardo]] had directed "onto a wrong line"<ref name=line>{{cite book | last = Jevons | first = William Stanley | author-link = :w:en:William Stanley Jevons | editor = R.D. Collison Black | date = 1970 | orig-date = 1871 | title = The Theory of Political Economy | location = Harmondsworth etc. | publisher = Penguin Books | url = https://archive.org/details/theoryofpolitic000jevo | url-access = registration }} Preface to second edition (1879), [https://archive.org/details/theoryofpolitic000jevo/page/72/mode/1up p. 72] (cited by {{harvnb|Dobb|1973|p=166}})</ref> and according to Stigler "his belief that all evil economic influences were incarnate in [[John Stuart Mill]]" is well-known. [[:w:en:Carl Menger|Carl Menger]] was an important Austrian founder of [[:w:en:Marginalism|Marginalism]] — see: "[[Creating Economics/History of Economic Thought/Menger and Austrian Economics|Menger and Austrian Economics]]." The third founding father of Marginalism was [[:w:en:Léon Walras|Léon Walras]], in Switzerland — see: "[[Economics/History of Economic Thought/Léon Walras and Vilfredo Pareto: General Equilibrium|Léon Walras and Vilfredo Pareto: General Equilibrium]]." == References == {{references}} == Sources == *{{cite book | last = Dobb | first = Maurice | date = 1973 | title = Theories of Value and Distribution Since Adam Smith: Ideology and Economic Theory | location = London | publisher = Cambridge University Press | ISBN = 0 521 20100 4 | url = https://archive.org/details/theoriesofvalued0000dobb | url-access = registration | ref = harv }} {{DEFAULTSORT:Neo-classical Economics}} [[Category:History of Economic Thought]] pinwrek947dtxdxj043dw4e16vkilhz 0 332288 2835397 2835233 2026-10-01T22:30:33Z Scogdill 1331941 2835397 wikitext text/x-wiki = Wedding of Miss Clarita de Murietta and the Duc de Santona = ==Overview== This wedding was between Spanish Catholics, but it took place in England. The de Murriettas were friends of the Prince of Wales, and many people from his social network in 1890 were present at this wedding. The Murrietas lived in the UK (in London, with a country estate in Surrey), but the Duc de Santona lived in Spain. ==Logistics== * The wedding took place at 11:30 on Wednesday, 29 January 1890 at Brompton Oratory. People invited to the church ceremony had tickets. The reception seems to have been a breakfast, but after the ceremony. * "The weather was all that could desired of a winter's day, presenting a bright and cheerful contrast to the storms which have lately proved so destructive and depressing. That is to say, the wind had moderated, the sun shone brightly, and the air was tinged with exhiliarating [sic] crispness. As early ten o'clock — an hour and half before the ceremony — the holders of tickets for admission to the sacred building began to arrive, and crowd to assemble round the gateways. At eleven every seat, except those reserved for the wedding party, was occupied, and from that time till nearly one o’clock a long line of carriages occupied both sides of the broad roadway from the Oratory to beyond South Kensington Museum."<ref name=":2">"Marriage of Miss de Murrieta to the Duke of Santona." ''Sussex Express'' 1 February 1890, Saturday: 7 [of 12], Cols. 1a–3a. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0000654%2F18900201&page=7&article=136&stringtohighlight=mandeville+viscount. Print title: ''The Sussex Express, Surrey Standard, Weald of Kent Mail, Hants and County Advertiser'', p. 7.</ref> ===Staff and Vendors=== *"The Bishop of Southwark, the Rev. Canon Searle (of Tunbridge Wells), the Rev. Father Gordon, of the Oratory, who performed the ceremony, entered the church in procession, with their attendants."<ref name=":2" /> *"An orchestra of nearly 40 string instruments, with the organ, performed for three-quarters of hour before the time fixed, 11.30."<ref name=":3" /> *"The music was as follows:— Before service, slow movement of minuet and trio for Italian Symphony (Mendelssohn) and Allegretto from 8th Symphony (Beethoven). As the bride entered the church, 'Bridal march' from Lohengrin. While the register was signed, offertoire from 'Messe Solennelle.' During Mass, Gounod's 'Mess Solennelle,' offertory, Gounod's 'Ave Maria,' solo by Master Hawkins. Finale, Mendelssohn’s 'Wedding March.'"<ref name=":2" /> ==Related Events== * The ''Bedfordshire Mercury'' reported that the Marques and Marquesa de Santurce hosted some notables at their London residence, 18, Carlton House-terrace.<ref name=":3" /> * Reception * Honeymoon ==Who Was Present== ===Bride and Bridesmaids=== ====Bride==== "Clarita de Murrieta, younger daughter of the Marques and Marquesa de Santurce, of Wadhurst Park, Sussex, and 18, Carlton House-terrace"<ref name=":2" /> ==== Bridesmaids ==== * Mdlle. Marie de Mitjans (sister of the bridegroom) * The Hon. Muriel Agnes Brassey (daughters of Lord Brassey, of Normanhurst) * The Hon. Marie Adelaide Brassey * Miss Joan Marion Nevill (daughter of Lord Henry Nevill) * Miss Violet Gathorne-Hardy (daughter of the Hon. C. C. and Lady Cicely Louisa Gathorne-Hardy) * Miss Constance Barron (daughter of Capt. and Mrs. Barron)<ref name=":3" /> ====Pages==== ===Groom and Best Man=== * "Juan Manuel Mitjans, Duque de Santona, a grandee of Spain"<ref name=":2" /> * "Mr Francis de Murrieta, cousin of the bride, was best man."<ref name=":3" /> ===People Who Attended=== "The company present at the wedding ceremony, and afterwards at the breakfast at Carlton House-terrace, included,"<ref name=":2" /> # The Prince of Wales # the Marquesa de Manzanedo and Mdlle. Maria Mitjans # the Duque and Duquesa de Lecera # the Duchess of Leinster and Lady Helen Duncombe # the Duchess of Manchester # the Dowager Countess of Airlie and Lady Griselda Ogilvy # [[Social Victorians/People/Mandeville|Viscountess Mandeville and Lord Kimbolton]] # Viscountess Hood # Lord and Lady Brooke and Lady Sybil St. Clair-Erskine # Lord and Lady William Nevill # Lord Brassey # Lord and Lady George Nevill # Hon. Thomas and Lady Idina Brassey # Lord and Lady Henry Nevill # the Bishop of Southwark # Lady Frances Pratt and Lady Clementine Pratt # Lady Lister-Kaye # Lady Dorothy Nevill # Lady Cicely Gathorne-Hardy # Lady Sandhurst # Lady Alice Morland # Lord Richard Nevill # Sir Frederick and Lady Milner # Hon. C. N. Spencer, M.P., and Mrs. Spencer # Mr. and Lady Margaret Douglas # Hon. Humphrey Sturt # Sir Oscar Clayton # Lady Constance Leslie and Miss Leslie # Sir William Gordon-Cumming # Hon. Mrs. Agar-Ellis and Miss Ellis # Mons. and Madame Escandon and Mdlle. Escandon # M. Calderon # M. Errazu # M. Galintz # Mr. Frank Lee # Major Swaine # Mr. and Mrs. Granville Ward # M. de Soveral # Mr. W. H. Mitchell # the Rev. Mr. Palmer # Mr. C. de Murrieta # Mr. A. de Murrieta # Mr. Mariano de Murrieta # Mr. C. J. de Murrieta # Mr. and Mrs. Barron # Mr. Hatch # Mr. Reginald Ronalds # Mrs. Temple Soanes # Dr. and Mrs. Robson Roose # Mr. and Mrs M. Van Raalte # Mr. Grenfell # Mrs. Bischoffsheim # Mr. Hulse, M.P., and Mrs. Hulse # Mr. Wood # Dr. White # Mrs. Ronalds and Mrs. Ritchie # Mr. Leo Schuster # Mrs. Ince Anderton # Mr. Eldrid # Mr. and Mrs. Hammond # Mr. and Mrs. E. H. Eldrid # the Rev. J. S. Welby # Mr. F. O. Smithers # Mr. and Mrs. Moreton Frewen # Mr. and Mrs. Granville Ward # Mrs. and Miss Silvertop # Mr. Gerald Paget # Mr. and Mrs. Hwfa Williams # Mr. Charles Van Raalte # Mr. Albert Stopford # Hon. Mrs. Vaughan # Miss E. Vaughan # Miss Townshend # Mrs. Coupland # Mrs. and Miss Leigh # Mr. and Mrs. F. V. Williams # the Spanish Consul-General ==What People Wore== <blockquote>The Bride. — The bride’s dress was of rich white Venetian brocade, with a very long court train; the front was bordered round the hem with fringes and bouquets of orange blossom, a garland of the same being arranged on the left side. The bodice had a high collar of delicate lace and a softly-draped fichu of lace and fine muslin. She wore small crown of orange-flowers and a tulle veil fastened to the hair with diamond ornaments and carried a lovely bouquet of exotics. The Bridesmaids. — The bridesmaids’ pretty costumes were of soft cream crepon, with sleeves and vests of apple green velvet; the straight skirts were edged with a single row of gold braid; and they wore sashes of pale mauve moiré, the ends of which fell from the waist in front to the feet. The two elder bridesmaids wore small bonnets of green velvet and gold braid, and the other four picturesque hats match, trimmed with the braid and several green ostrich feathers. The bridegroom's gift to each bridesmaid was also worn. It was a very handsome brooch formed of a horseshoe in diamonds and sapphires pierced by a diamond arrow; in the centre of the horseshoe were the initials "J. C." in diamonds, with a ducal coronet above in rubies and diamonds. The bridesmaids carried bouquets of lilies of the valley and green orchids, tied with mauve and green ribbons. The Bride’s Mother. — The Marquesa de Santurce's costume was entirely of dark reseda velvet, with the exception of the sleeves, which were of embossed silk with a design of foliage delicately outlined in gold. The straight collar was also of embossed brocade. The Marquesa’s bonnet was composed of two wing-like arrangements of reseda-green lisse, wrought with lines of gold, placed eave-like over the wearer's dark hair. The crown, a very tiny one, almost hidden by the wings, was of velvet embroidered in gold. The bouquet carried was an exquisite combination of white orchids, Maréchal Niel roses, and mimosa. It was tied with ribbon of the same colour as the costume. The Bridegroom's Mother. — The Marquesa de Manzanedo, the bridegroom’s mother, wore train of almost courtly proportions. It, as well as the bodice, was of dark heliotrope velvet. The bodice was made with puffed sleeves, very high on the shoulders, and a Medici collar This was faced, and the bodice bordered, with Russian sable. The skirt was of pearl-coloured brocade, backed with plaler heliotrope. It was deeply flounced with dark rich sable tail, and over it at one side a scarf of priceless Spanish lace was draped. A bonnet of lisse and velvet in corresponding tones of heliotrope colour was worn. The Marquesa carried a magnificent bouquet of orchids of the same shade her costume, arranged with varied foliage and tied with dark heliotrope ribbon. The Bridegroom's Sister.—The Duquesa de Lecera, the bridegroom's sister, was attired in a striking costume of pale pink satin striped with black. It was princess in form the stripes symetrically converging towards the waist. The skirt was bordered with soft ruche of pale pink chiffon. A pretty little bonnet composed of lisse and velvet matched the dress, and the Duquesa carried a bouquet of pale pink carnations and orchids. The Bride’s Sister.—Lady William Nevill’s dress was of Sicilienne and velvet. The form was of the polonaise order and the colour serpent-green. The skirt was quite plainly arranged, and entirely of Sicilienne. Lady William’s bonnet was of velvet, a ruche of pale pink China crêpe showing above the hair. Pink and green ospreys were placed at one side. Her bouquet was mass of pink blossoms arranged with fern fronds, and tied with serpent-green ribbon. Lady Cicely Gathorne-Hardy's dress was a pretty combination of electric-blue velvet and cashmere. There was soft vest of white China crêpe. The bonnet was of velvet, similar that of the dress; a grey and white bird was coquettishly placed at one side. Lady Cicely’s bouquet was of white roses and pink carnations. Lady Henry Nevill’s dress was made of light cloth of a pale tone of fawn-colour striped with narrow lines of brown. The sleeves and top portion of the bodice were of violet velvet. pointed panel of similar velvet showed at either side of the skirt. The cloth was drawn in folds  over the shoulders, and was caught under folds of velvet at the waist, showing deep V-shaped points of the bright-hued velvet in front and at the back. A bonnet of fawn-coloured silken gauze was covered with violet velvet pansies laid flatly on the crown. Lady Henry's bouquet was of shaded violets. Lady George Nevill wore a long mantle of dark-brown cloth broché with red. The sleeves, made high at shoulders were of dark autumnal-brown velvet, and the bonnet was of velvet, of the same colour, amid loops of which dark-red plumaged birds were nestled. Lady Idina Brassey's costume of ruby velvet was very effective, being flounced and bordered with dark fur. The hat was of felt, matching the dress in colour, and its flat crown was surrounded with dark red ostrich feathers. Lady Rose Leigh was quietly dressed in a neat tailor-made tweed gown, dark blue in colour, intercepted by narrow lines of white. A hat of dark blue felt, bordered with cock’s feathers twisted into a curl over the flat crown, looked appropriate to the studied simplicity of the dress. Lady Dorothy Nevill was attired in a long mantle of wall-flower red plush trimmed with bronze passementerie. Her headgear was a neat, closely-fitting bonnet, matching her mantle in color. The Duchess of Manchester wore a dress of silver-grey silk brocaded with satin; a section of plain satin, arranged in straight pleats, formed the back. Her Grace's mantle was of velvet — of so dark a shade of [Col. 1c–2a] myrtle green as to appear black in the shadow — and it was trimmed with lines of jet embroidery. The bonnet worn by the Duchess was of sinrlar velvet, with a spray of jet across the front. The Duchess of Leinster, who was accompanied by her sister, Lady Helen Duncombe, was attired in golden brown cloth trimmed with a design of foliage in velvet, applied to the surface of the cloth, with silk embroidery. Her Grace’s coat was of embossed silk of a delicate shade of stone colour slightly wrought with gold. The pretty but very small hat worn by the duchess was of brown felt, and her Grace's boa of ostrich feathers shaded from brown to pale stone colour. Lady Helen’s dress was of dark reddish brown woollen material, simple in form but of perfect style. Her hat was also of felt, matching her costume in colour. Lady Algernon Gordon Lennox. — A strikingly-handsome costume was that worn by Lady Algernon Gordon-Lennox. It was of bright soft-red velvet trimmed with bands of red-gold embroidery. Her bonnet was a very small one of red velvet, with a spray of ferns  simulated in jet across the front. Lady Algernon wore a long boa of sable-tail. The Dowager Countess Airlie. — Was costumed in her invariable sable robes of almost cloister-like severity, which so admirably suit her distinguished figure and beautiful face. Lady Grisel [Griselda?] Ogilvy. — Wore a black skirt, with a broad sash of pale blue moire. Her cape was of fine steel beadwork, and she wore a Henry VIII. hat of black velvet, with a group of pale blue feathers at one side. Mrs. Ronalds. — Wore a dress and mantle of black velvet bordered with sable tail, and a bonnet ''en suite''. Her daughter, Mrs. Ritchie. — Was gowned in willow-green Royal silk, and wore a bonnet of green lisse and mantle made entirely of jet beadwork.<ref name=":2" /></blockquote>The bride's going-away dress: "The bride went away in a costume of grey velvet, of a delicate shade, draped with ''Sicilienne'', and trimmed with rich steel passementerie; a broad band  of grey velvet edged the skirt, and she wore a jacket and hat to match, and sable boa and muff."<ref name=":2" /> ==Gifts== <blockquote>THE WEDDING PRESENTS Were displayed in the ball-room, at the house of the Marquess De Santurce in Carlton House Terrace. The jewellery was simply magnificent, and the others were also costly and elegant. The presents to bride and bridegroom numbered about 500, including the following:—<ref name=":2" /> [set as unordered list, originally set as separate paragraphs] TO THE BRIDE * The P<small>RINCE</small> and P<small>RINCESS</small> of W<small>ALES</small>, moonstone heart brooch, set with rubies and diamonds. * Princess L<small>OUISE</small>, Duchess of Fife, and the Duke of F<small>IFE</small>, a set of silver salt-cellars. * The Empress E<small>UGENIE</small>, a large silver mirror. * The B<small>RIDEGROOM</small>, a magnificent sapphire and diamond necklace, a sapphire and diamond bracelet, ruby and diamond ring, pearl double-heart brooch, diamond pin, diamond and pearl brooch, gold and pearl studs, and gold-handled hunting crop. * The Marquess and Marquesa <small>DE</small> S<small>ANTRUCE</small> [sic], a magnificent diamond tiara. * Marquesa <small>DE</small> S<small>ANTURCE</small>, diamond half-hoop ring. * M. M<small>ITJANS</small>, father of the bridgegroom, three rows of large pearls, with diamond and emerald clasp. * Marquesa De M<small>ANZANEDO</small>, mother of bridgeroom [sic], ruby and diamond cluster necklace. * Lord and Lady W<small>ILLIAM</small> N<small>EVILL</small>, handsome dressing bag with tortoiseshell and gold fittings, and enamel and diamond watch bracelet. * Mr. C<small>HRISTOBAL</small> and Mr. A<small>DRIANO DE</small> M<small>URRIETA</small>, diamond aigrette, and two pairs of carriage horses. * Mr. M<small>URIANO DE</small> M<small>URRIETA</small>, silver-gilt tea service and tray, three silver-gilt candelabras, and set of silver-gilt dessert plates. * The Duc and Duchesse <small>DE</small> V<small>ISTAHAMOSA</small>, complete set of silver-gilt dessert forks, knives, and spoons, and four pairs of old English silver candlesticks. * Mr. F<small>RANCIS</small> and Mr. C. J. <small>DE</small> M<small>URRIETA</small>, pair of large silver-gilt repoussé dishes. * Marques <small>DE LA</small> T<small>ORREVILLE</small>, diamond double-heart  brooch. * M. C<small>ALDERON</small>, set of diamond hair pins. * Marchioness of A<small>BERGAVENNY</small>, black point lace and tortoiseshell fan, with monogram in rubies and diamonds. * Duke and Duchess of N<small>EWCASTLE</small>, diamond and emerald watch-bracelet. * Mr. A<small>LFRED DE</small> R<small>OTHSCHILD</small>, diamond and pearl bracelet. * Lord and Lady S<small>ANDHURST</small>, gold "1890" sleevelinks. * Mdlle. M<small>ARIA</small> M<small>ITJANS</small>, large carbuncle and diamond pendant. * The S<small>PANISH</small> A<small>MBASSADOR</small>, six silver coffee cups. * Duchess of M<small>ANCHESTER</small>, pair of silver-gilt-topped scent bottles. * Duchess of L<small>EINSTER</small>, old china box. * Hon. R<small>OBERT</small> and Mrs. S<small>PENCER</small>, diamond pin. * Marquis of A<small>BERGAVENNY</small>, writing set and candlestick. * Countess of D<small>ENBIGH</small>, embroidered silk blotting book. * Lady A<small>LICE</small> M<small>ORLAND</small>, silver vase. * Lord R<small>ICHARD</small> N<small>EVILL</small>, pigskin luncheon bag with complete silver fittings. * Hon. T<small>HOMAS</small> and Lady I<small>DINA</small> B<small>RASSEY</small>, leather carriage card case, with gold mountings and monogram. * Lord and Lady B<small>ROOKE</small>, Dutch silver ornament. * Viscount and Lady V<small>IOLET</small> D<small>ANGAN</small>, old painted snuff-box. * Sir O<small>SCAR</small> C<small>LAYTON</small>, pair of silver ash trays. * Sir W<small>ILLIAM</small> G<small>ORDON</small> C<small>UMMING</small>, silver-headed scent bottle. * Viscountess M<small>ANDEVILLE</small>, small green leather travelling bag. * Mrs. C<small>OUPLAND</small>, silver crucifix. * Canon S<small>EARLE</small>, benetier. * Lady B<small>ROUGHAM</small> and V<small>AUX</small>, old gold-mounted scent  bottle. * Lady C<small>LIFFORD</small> and Miss T<small>OWNELEY</small>, silver looking-glass. * Lord A<small>SHBURTON</small>, silver box. * Lady A<small>LGERNON</small> G<small>ORDON</small>-L<small>ENNOX</small>, inlaid tortoiseshell box. * Dowager Duchess of N<small>EWCASTLE</small>, silver tray. * Lord and Lady C<small>HARLES</small> B<small>ERESFORD</small>, small Louis XVI table. * Sir F<small>REDERICK</small> and Lady M<small>ILNER</small>, silver tray. * Sir Bach Cunard, scent bottle with gold top set with diamonds. * Mrs. G. C<small>AVENDISH</small>-B<small>ENTINCK</small>, pair of small old silver vases. * Mr. and Mrs. E<small>DWARD</small> S<small>ASSOON</small>, Sevres china ink-stand. * Mr. J. B. and Lady R<small>OSE</small> L<small>EIGH</small>, Chippendale table. * Lord and Lady H<small>ENRY</small> N<small>EVILL</small>, complete silver tea set. * Mr. H<small>ORACE</small> F<small>ARQUHAR</small>, two girandoles. * Colonel R<small>ALPH</small> V<small>IVIAN</small>, umbrella with gold handle. * T<small>HE</small> S<small>ERVANTS AT</small> W<small>ADHURST</small> PA<small>RK AND</small> 18, C<small>ARLTON</small> H<small>OUSE-TERRACE</small>, large silver salver. * T<small>HE</small> W<small>ADHURST</small> T<small>ENANTS AND</small> T<small>RADESMEN</small>, large silver cup. * W<small>ADHURST</small> P<small>ARK</small> S<small>TABLEMEN</small>, driving whip and hunting crop. * Marquis C<small>AMDEN</small> and Lady C<small>LEMENTINE</small> P<small>RATT</small>, silver box. * Mr. R<small>ICARDO DE LA</small> Q<small>UININA</small>, Minton china tea and coffee set and dinner service. * Mr. H<small>EREDIM</small>, diamond and enamel watch bracelet. * Duque and Duquesa <small>DE</small> L<small>ACERA</small>, diamond and sapphire brooch. * Mr. and Mrs. D. Y<small>BARROMDO</small>, large silver bowl. [Col. 2c–3a] * Mr. F. V. and Miss W<small>ILLIAMS</small>, four silver-gilt salt cellars. * Miss L<small>EIGH</small>, leather letter holders. * Duqe and Duquesa <small>DE</small> F<small>ERNAN</small>-N<small>UNEZ</small>, old Spanish fan. * Duque and Duquesa <small>DE</small> A<small>LBA</small>, old Spanish fan. * Mrs. and the Misses C<small>ARROLL</small>, silver hand-glass. * Lord George N<small>EVILL</small>, hunting crop. * Lady George N<small>EVILL</small>, silver photo frame. TO THE BRIDEGROOM. * The Bride, turquoise and diamond pin, and ruby and diamond ring, and Cabochen sapphire and diamond sleeve links. * The Marquesa <small>DE</small> M<small>ANZANEDO</small>, emerald and diamond  pin. * The Marquesa <small>DE</small> S<small>ANTURCE</small>, a brougham, sapphire and diamond pin, and ruby and diamond horseshoe pin. * Mr. C. and Mr. A. <small>DE</small> M<small>URRIETA</small>, pair of guns. * Lord and Lady W<small>ILLIAM</small> N<small>EVILL</small>, set of crystal and silver liqueur cups and bottles on crystal and silver tray. * Mr. F<small>RANCIS DE</small> M<small>URRIETA</small>, silver looking-glass. * Mr. C. J. <small>DE</small> M<small>URRIETA</small>, pearl pin. * Count T<small>ORRE</small>-A<small>RIAS</small>, silver-mounted paper knife. * Comte <small>DE LA</small> P<small>ATELLA</small>, pearl pin.   * Count <small>DE</small> B<small>ENATUA</small>, Rahi [?] cart. * The Duque and Duquesa <small>DE</small> L<small>ECERA</small>, gold links and studs. * Duc <small>DE</small> A<small>LBA</small>, phaeton. * Mr. J. G<small>RENFELL</small>, silver cigarette case. * Mr. T<small>HOMAS</small> W<small>OOD</small>, umbrella and cigar case. * Lord R<small>ICHARD</small> N<small>EVILL</small>, leather box, containing cards, counters, &c. * Mr. P. <small>DE</small> G<small>ALINDEZ</small>, silver cigar case. * Madame <small>DE LOS</small> H<small>EROS</small>, tea basket. * Duchesse <small>DE</small> A<small>LIAGA</small>, set of books. * M. and Madame E<small>SCAUDON</small>, sapphire and diamond pin. * Count E<small>STRADOS</small>, gold match-box. * M. R<small>AMON DE</small> E<small>RRAZU</small>, silver-fitted dressing bag. * M. L<small>UTS DE</small> E<small>RRAZU</small>, diamond pin. * Sir W<small>ILLIAM</small> G<small>ORDON</small>-C<small>UMMING</small>, old silver box. * The S<small>ERVANTS</small> at Wadhurst and 18, Carlton House-terrace, pair of silver-mounted riding whips.<ref name=":2" /> </blockquote> ===Unusual or Interesting Gifts=== ==Anthology== The Marques and Marquesa of Santurce hosted the wedding and reception of their daughter, Miss Clarita de Murietta, with the Duc de Santona. ==== The House Party ==== This ''Bedfordshire Mercury'' reports on the wedding and what seem to be local celebrities. Given the focus on [[Social Victorians/People/Louisa Montagu Cavendish|Louisa, Duchess of Manchester]] and her daughter-in-law [[Social Victorians/People/Mandeville|Consuelo, Lady Mandeville]], the ''Bedfordshire Mercury'' looks like a paper local to them.<blockquote>The Duchess of Manchester, Vicountess Mandeville and Lord Kimbolton were among the guests entertained by the Marques and Marquesa de Santurce at their residence, Carlton House-terrace, London, on the occasion of the marriage of their younger daughter, Mdlle. Clarita de Murrieta, with the Due de Santona, last Wednesday. The ceremony took place at Brompton Oratory, where the floral decorations were most elaborate, whole trees of white lilac and camelias, besides a profusion of arums and lilies of the valley, being artistically arranged about the sanctuary and in adjacent chapels. An orchestra of nearly 40 string instruments, with the organ, performed for three-quarters of hour before the time fixed, 11.30. The bridesmaids were Mdlle. de Mitjans (sister of the bridegroom), the Hon. Muriel and Hon. Marie Brassey, Miss Joan Nevill, Miss Violet Gathorne-Hardy, and Miss Constance Barron. Mr Francis de Murrieta, cousin of the bride, was best man. The Bishop of Southwark performed the nuptial rite, and afterwards said Mass, assisted by the Rev. W. F. Gordon, and other Fathers; Gounod’s "Messe Solennelle" was sung by nearly 40 voices, and his "Ave Maria," adapted from Bach, by a Master Hawkins. The Prince of Wales, the Duchess of Leinster and Lady Helen Duncombe, Viscountess Hood, Lady Frances and Lady Clementine Pratt, the Hon. C. R. and Mrs Spencer, Mr Grenfell, Mr and Mrs Hulse, &c., were also of the bridal company. The Duchess of Manchester wore at the church a long velvet mantle trimmed with sable, which almost concealed her grey dress. The donors of wedding presents included the Empress Eugénie, the Prince and Princess of Wales, the Duke and (Princess Louise) Duchess of Fife, Mr Alfred Rothschild, &c. The Duchess of Manchester gave the bride a pair of silver-gilt-topped scent bottles, and Lady Mandeville a small green leather travelling bag. The Duc de Santona and his bride left town for Wadhurst Park.<ref name=":3">"Kimbolton." ''Bedfordshire Mercury'' 1 February 1890, Saturday: 8 [of 8], Col. 3b [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0001290%2F18900201&page=8&article=101&stringtohighlight=mandeville+viscount. Same print title and p.</ref></blockquote> ==== The Wedding ==== This report from the ''The Sussex Express, Surrey Standard, Weald of Kent Mail, Hants and County Advertiser'' takes up about 2 1/3 full columns:<blockquote>The marriage was solemnised, on Wednesday, at Brompton Oratory, with imposing ceremonial, and under most auspicious circumstances, of Juan Manuel Mitjans, Duque de Santona, a grandee of Spain, to Clarita de Murrieta, younger daughter of the Marques and Marquesa de Santurce, of Wadhurst Park, Sussex, and 18, Carlton House-terrace. The [happy event?] we now record not only attracted a numerous and brilliant congregation of the fashionable world to the service at the Oratory and the subsequent festivities, but was [invested?] with considerable interest to the wide borders of Kent and Sussex, from the sea to beyond the Weald, the bride being connected by the marriage of her sister to Lord William Nevill, last year, with the noble local families of Nevill, Gathorne-Hardy, Brassey, and Egerton. Her father, too, the Marques de Santurce, is now quite a Sussex man, having for years past been seated at Wadhurst Park. The weather was all that could desired of a winter's day, presenting a bright and cheerful contrast to the storms which have lately proved so destructive and depressing. That is to say, the wind had moderated, the sun shone brightly, and the air was tinged with exhiliarating [sic] crispness. As early ten o'clock — an hour and half before the ceremony — the holders of tickets for admission to the sacred building began to arrive, and crowd to assemble round the gateways. At eleven every seat, except those reserved for the wedding party, was occupied, and from that time till nearly one o’clock a long line of carriages occupied both sides of the broad roadway from the Oratory to beyond South Kensington Museum. The interior of the church, long before the arrival of the bride, presented a brilliant appearance. Rays of sunshine from the clerestory windows brought into relief the beautiful floral decorations within the sanctuary. Groups of tall palms and camellia trees in blooms, interspersed with white lilac and arum lilies, were placed in front of the chancel, while on the fine marble balustrade were large brass bowls filled with white azaleas, lilies of the valley, and roses. Between the massive columns separating the transepts from the aisles, were also palms and ferns interspersed with rose-tinted camellias and other flowers. The altars were also richly decorated. On the high altar were eight large bouquets of choice white exotics. The altar of Our Lady in the East transept was decked in bouquets of white, orange, and a pale shade of yellow, while that of St. Philip the west transept, was arranged with palms and scarlet and white blooms. THE CEREMONY. The choral part of the service commenced at eleven o’clock, when the choir, numbering about one hundred performers, including trumpeters and stringed instrumentalists, commenced a programme of grand sacred music. The Duke de Santona, who was attended by the bride’s cousin, Mr. Francis Murrieta, as best man, arrived several minutes before the half-hour, and awaited, at a ''prie-Dieu'' placed in front of the chancel balustrades, the coming of his ''fiance'' [sic]. The bridesmaids reached the Oratory just afterwards in readiness to take their part in the bridal procession. They were Miss Marie Mitjans (sister of the bridegroom), Miss Joan Marion Nevill (daughter of Lord Henry Nevill), Miss Violet Gathorne-Hardy (daughter of the Hon. C. C. and Lady Cicely Louisa Gathorne-Hardy), Miss Barron (daughter of Capt. and Mrs. Barron), the Hon. Muriel Agnes Brassey,  and the Hon. Marie Adelaide Brassey (daughters of Lord Brassey, of Normanhurst). Then came the Prince of Wales, who had journeyed from Sandringham specially for the occasion. His Royal Highness, attended by  Colonel Teesdale, was conducted to a seat in front of the sanctuary. The Bishop of Southwark, the Rev. Canon Searle (of Tunbridge Wells), the Rev. Father Gordon, of the Oratory, who performed the ceremony, entered the church in procession, with their attendants, from the north door of the west transept, and took their position in front of the high altar. The bride was accompanied to church by her mother, and the Marques de Santurce received his daughter at the main entrance to the nave. The bridal procession was at once formed. The fair and stately bride — fairer than most of the daughters of the sunny south — was escorted by her father through the nave and transepts to the ''prie-Dieu'' in front of the entrance to the sanctuary, the bridesmaids following, and the instrumental part of the choir performing the spirited bridal match [sic] from Lohengrin. During the first few minutes of the holy ceremony, the bride and bridegroom remained in prayer in front of the chancel. They were then conducted to the altar, before which, the marriage service was celebrated. It occupied but a few minutes[.] The clergy, the bride and bridegroom, the Prince of Wales, the parents of the happy pair, and several of their nearest relatives repaired to the vestry to sign the register. The Prince gave his arm to the Marquesa de Santurce, and signed the register as one of the witnesses. On returning to the church Nuptial Mass was celebrated, and the whole service which occupied less than an hour, was brought to a conclusion by the Bishop bestowing the blessing of the Church upon the young couple. The music was as follows:— Before service, slow movement of minuet and trio for Italian Symphony (Mendelssohn) and Allegretto from 8th Symphony (Beethoven). As the bride entered the church, "Bridal march" from Lohengrin. While the register was signed, offertoire from "Messe Solennelle." During Mass, Gounod's "Mess Solennelle," offertory, Gounod's "Ave Maria," solo by Master Hawkins. Finale, Mendelssohn’s "Wedding March." THE DRESSES OF THE LADIES. ... THE WEDDING GUESTS. ... THE WEDDING BREAKFAST Was served at the residence of the parents of the bride, 18, Carlton House-terrace. The Prince of Wales arrived there soon after the bride and bridegroom, when the Hungarian band, stationed in the corridor at the top of the grand staircase, played the "National anthem." Here, again, the floral decorations were superb. The table at which the Prince of Wales sat, with the bride and groom and their immediate relatives, was a mass of white and gold. The bridal colouring was supplied in the first instance by the colossal frosted structure of the cake, flanked by crescents of white orchids, orange flower, and branches of orange trees, bearing double burdens of fruit and bloom. The other six tables in the dining-room were decorated with white and the palest of blush pink, a favourite colour with the bride. The principal drawing-room was made to appear almost tropical with gorgeously-hued orchids and foliage, combining tints of vivid scarlet and bright yellow, with hundreds of shades of tender green. A stand of white lilies and pink roses placed in the entrance hall was much and deservedly admired. Nor were the charms of a second drawing-room, adorned with dozens upon dozens of double and single daffodils, passed over in silence. In the ball-room where the wedding presents were "on view," was an atmosphere laden with the subtle sweetness of fair white lilies. everywhere [sic] there were flowers, and the effect, combined with that of the brilliant sunshine which crowned the day, was to banish the recollection of January and suggest a vision of June. About three o’clock the Duque de Santona and his bride left by special train for Wadhurst Park, where they will pass the early days of the honeymoon. The bride went away in a costume of grey velvet, of a delicate shade, draped with ''Sicilienne'', and trimmed with rich steel passementerie; a broad band  of grey velvet edged the skirt, and she wore a jacket and hat to match, and sable boa and muff. THE WEDDING PRESENTS ...</blockquote>This report from the ''Tunbridge Wells Journal'' is a good example of a regional paper covering an event from a local perspective.<blockquote>On Wednesday morning, the Brompton Oratory was crowded to witness the nuptials of Miss Clarita de Murietta, daughter of the Marques and Marquesa de Santurce, of Wadhurst Park, Sussex, and Carlton House terrace, and the Duc de Santona. The event was invested with considerable interest to Kent and Sussex, the bride being connected by the marriage of her sister to Lord W. Nevill, with the families of Nevill, Gathorne-Hardy, Brassey, and Egerton. The Oratory was beautifully decorated with palms and ferns and white flowers. The service was fully choral and during the celebration of the nuptial mass selected music was rendered. The Prince of Wales, attended by Colonel Teesdale, was present. The Bishop or Southwark, assisted by Father Gordon and the Fathers of the Oratory, officiated. The bridge [sic] was conducted to the high altar by her father, the Marques de Santurce, who gave her away. A cousin of the bride, Mr Francis de Murietta, accompanied the Duc de Santona as best man. The bridesmaids wore dresses of soft cream crêpon, with sleeves and vests in vert pomme velvet edged with gold braid, straight skirts edged with the same, and slashes of pale mauve moiré. Two of the bridesmaids wore bonnets and the other four hats of green velvet  ornamented with gold braid and green ostrich feathers. The bridegroom's presents were a diamond arrow piercing a diamond and sapphire horseshoe, surmounted by ducal coronet in rubies and diamonds, and a "good-year" bouquet of lilies of the valley and green orchids tied with mauve streamers. The bridesmaids were Mdlle. Mara [?] Mitzans [s/b Mitjans], slater of the bridegroom, Miss Constance Barrow, daughter of Captain and Mrs Barrow, Miss Ivan Marion Nevill, daughter of Lord and Lady H. G. R. Nevill, Miss Violet Gathorne-Hardy, daughter of the Hon. C. G. and Lady Cicely Louisa Gathorne-Hardy, the Hon. Muriel Agnes Brassey, and the Hon. Marie Adelaide Brassey, daughters of Lord Brassey. The bride's dress was of rich white Venetian brocade, with long train, the front being bordered with fringes and bouquets of orange blossoms. The bodice had a high collar of lace, and a fichu of lace and fine muslin, softly draped. She wore a small crown of real orange blossoms, surmounted by a fine tulle veil. After the ceremony, the wedding party proceeded to 18, Carlton House terrace, the town residence of the Marques and Marquisa de Santurce, where a déjeuner and reception were held, the Hungarian band playing selected airs on the grand staircase. The honeymoon is to be spent at Wadhurst Park. The bride's going away dress was of a delicate shade of grey velvet, draped with Siciliéune, and trimmed with rich steel passementerie, with hat to match. The following is a list of the more important presents:— [Col. 6b–c] To the Bride. —<ref name=":1">"Marriage of Miss de Murietta." ''Tunbridge Wells Journal'' 6 February 1890, Thursday: 2 [of 8], Col. 6b–c [of 6]. ''British Newspaper Archive'' https://www.britishnewspaperarchive.com/image-viewer?issue=BL%2F0004632%2F18900206&page=2&article=036&stringtohighlight=mandeville+viscount. Same print title and p.</ref> [gifts list below set as unordered list to make it easier to read] * From the Prince and Princess of Wales, moonstone heart brooch, set with rubies and diamonds; * Princess Louise, Duchess of Fife, and the Duke of Fife, a set of silver-gilt salt cellars; * the Empress Eugénie, a large silver mirror; * the bridegroom, a magnificent sapphire and diamond necklace, a sapphire and diamond bracelet, ruby and diamond ring, pearl double-heart brooch, diamond pin, diamond and pearl brooch, gold and pearl studs, and gold-handled hunting crop; * the Marques and Marquesa de Santurce, a magnificent diamond tiara; * Marquesa de Santurce, diamond half-loop ring; * M. Mitzans, father of the bridegroom, three rows of large pearls, with diamond and emerald clasp; * Marquesa de Manzanedo, mother of bridegroom, ruby and diamond cluster necklace; * Lord and Lady William Nevill, handsome dressing bag with tortoiseshell and gold fittings, and enamel and diamond watch bracelet; * Mr Christobal and Mr Adriano de Murietta, diamond aigrette, and two pairs of carriage horses; * Mr Muriano de Murietta, silver-gilt tea service and tray, three sliver-gilt candelabras, and set of silver-gilt dessert plates; * the Duc and Duchesse de Vistahamosa, complete set of silver-gilt dessert forks, knives and spoons, and four pairs of old English silver candlesticks; * Mr Francis and Mr C. J. de Murietta, pair of large silver-gilt repoussé dishes; * Marquess de Ia Torreville, diamond double-heart brooch; * M. Calderon, set of diamond hairpins; * Marchioness of Abergavenny, black point lace and tortoiseshell fan, with monogram in rubies and diamonds; * Duke and Duchess of Newcastle, diamond and emerald watch-bracelet; * Mr Alfred de Rothschild, diamond and pearl bracelet; * Lord and Lady Sandhurst, gold "1890" sleeve links; * Mdlle. Maria Mitzans, large carbuncle and diamond pendant; * the Spanish Ambassador, six sliver coffee cups; * Duchess of Manchester, pair of silver-gilt-topped scent bottles; * Duchess of Leinster, old china box; * Hon. Hobert and Mrs Spencer, diamond pin; * Marquess of Abergavenny, writing set and candlestick; * Countess of Denbigh, embroidered silk blotting book; * Lady Alice Morland, silver vase; * Lord Richard Nevill, pigskin luncheon bag, with complete silver fittings; * Hon. Tomas and Lady Idina Brassey, leather carriage card-case with gold mountings and monogram; * Lord and Lady Brooke, Dutch silver ornament; * Viscount and Lady Violet Dangen, old painted snuff box; * Sir Oscar Clayton, pair of silver ash trays; * Sir William Gordon Cumming, silver-headed owl scent bottle; * [[Social Victorians/People/Mandeville|Viscountess Mandeville]], small green leather travelling bag; * Mrs Coupland, silver crucifix; * Canon Searle, benetier [font for holy water]; * Lady Brougham and Vaux, old gold-mounted scent bottle; * Lady Clifford and Miss Towneley, silver looking-glass; * Lord Asburton, silver box; * Lady Algernon Gordon Lennox, inlaid tortoiseshell box; * Dowager Duchess of Newcastle, silver tray; * Lord and Lady Charles Beresford, small Louis XVI. table; * Sir Frederick and Lady Milner, silver tray; * Sir Bache Cunard, scent bottle with gold top set with diamonds; * Mrs G. Cavendish-Bentick [sic], pair of small old silver vases; * Mr and Mrs  Edward Sassoon, Sèvres china inkstand; * Mr J. B. and Lady Rose Leigh, Chippendale table; * Lord and Lady Henry Nevill, complete silver tea set; * Mr Horace Farquhar, two girandoles; * Colonel Ralph Vivian, umbrella with gold handle; * the servants at Wadhurst Park and 18, Carlton House terrace, large silver salver; * the Wadhurst tenants and tradesmen, large silver cup; * Wadhurst Park stablemen, driving whip and hunting crop. To the Bridegroom. — * From the bride, turquoise and diamond pin, ruby and diamond ring; * Marquesa de Santurce, a brougham, sapphire and diamond pin, ruby and diamond horseshoe pin; * Mr C. and Mr A. de Murietta, pair of guns; * Lord and Lady William Nevill, set of crystal and sliver liqueur cups and bottles on crystal and silver tray; * Count Terro-Arias, silver-mounted paper knife; * Duc de Alba, phaeton; * Mr J. Grenfell, silver cigarette case; * Lord Richard Nevill, leather box, containing cards, counters, &c.; * Sir W. Gordon Cumming, old silver box; * Duchess de Alto, set of books; * M. and Mdme. Escandon, sapphire and diamond pin; * Count Estrados, gold match box.<ref name=":1" /> </blockquote> == Notes and Questions == # ==References== {{reflist}} 2xkc1ccnk0lftlc2056x4tc5kuiokp9 3 332297 2835335 2026-10-01T12:25:31Z MathXplore 2888076 advert1 ([[m:User:ZbVl/VD|Vandoom]]) 2835335 wikitext text/x-wiki == 2026-10-01 == <div class="mw-content-ltr" dir="ltr" style="text-align: left" lang="en">[[File:Information.svg|25px|alt=Information icon]] Hello. Apologies for writing this in English, but I wanted to let you know that one or more of [[Special:Contributions/NwSepticservices|your recent contributions]] have been undone because they appeared to be promotional. [[:m:en:WP:SOAPBOX|Advertising or using <span style="white-space:nowrap">Wikiversity</span> as a "soapbox"]] are not permitted. Take a look at the welcome pages to learn more about <span style="white-space:nowrap">Wikiversity</span>. Thanks. </div><!-- Glow-advert1 @ 1790857527476.9s --><nowiki></nowiki> [[User:MathXplore|MathXplore]] ([[User talk:MathXplore|discuss]] • [[Special:Contributions/MathXplore|contribs]]) 12:25, 1 October 2026 (UTC) 9qht5rnscrgpwtlr8f094sv88gkwi2r 0 332299 2835376 2026-10-01T19:42:34Z The Citer 3110681 Created page with "[[File:Nemertodermatida species.png|thumb|300x300px|Many species of Xenacoelomorphs.]] *Name Meaning: Strange hollow form *English Common Name: Xenacoelomorphs *Major distinguishing characteristics: Ciliated deuterostome *Approximate number of species described: 435 ==Phylogeny== This is a phylogenetic picture of Xenacoelomorphs: {{clade |label1='''Xenacoelomorpha''' |1={{clade |label1=''Xenoturbella'' |1={{clade |label1=Shallow clade |1={{clade..." 2835376 wikitext text/x-wiki [[File:Nemertodermatida species.png|thumb|300x300px|Many species of Xenacoelomorphs.]] *Name Meaning: Strange hollow form *English Common Name: Xenacoelomorphs *Major distinguishing characteristics: Ciliated deuterostome *Approximate number of species described: 435 ==Phylogeny== This is a phylogenetic picture of Xenacoelomorphs: {{clade |label1='''Xenacoelomorpha''' |1={{clade |label1=''Xenoturbella'' |1={{clade |label1=Shallow clade |1={{clade |label1= |1=''Xenoturbella japonica'' [[File:Xenoturbella japonica.jpg|60px]] |2={{clade |label1= |1=''Xenoturbella bocki'' [[File:Xenoturbella bockii longitudinal section English.svg|60px]] |2=''Xenoturbella hollandorum'' [[File:Xenoturbella hollandorum.jpg|60px]] }} }} |label2=Deep clade |2={{clade |label1= |1=''Xenoturbella monstrosa'' [[File:Xenoturbella monstroa (group).jpg|60px]] |2={{clade |label1= |1=''Xenoturbella churro'' [[File:Xenoturbella churro.jpg|60px]] |2=''Xenoturbella profunda'' [[File:Xenoturbella profunda.jpg|60px]] }} }} }} |label2=Acoelomorpha |sublabel2=(may be a phylum or a subphylum) |2={{clade |label1=Acoela |1={{clade |label1= |state1=dashed |1=Actinoposthiidae [[File:Pseudactinoposthia parva.gif|60px]] |state2=dashed |2=Antigonariidae [[File:Antigonaria arenaria.jpg|60px]] |state3=dashed |3=Antroposthiidae [[File:Antroposthia axi.jpg|60px]] |4=Diopisthoporidae |state5=dashed |5=Nadinidae |state6=dashed |6=Paratomellidae |state7=dashed |7=Taurididae |8={{clade |label1= |1=Paratomellidae |label2=Bursalia |2={{clade |label1=Prosopharyngida |1={{clade |label1= |1=Hallangiidae |2={{clade |label1= |1=Hofsteniidae |2=Solenofilomorphidae }} }} |label2=Crucimusculata |2={{clade |label1= |1=Proporidae [[File:Proporus sp.png|60px]] |2={{clade |label1= |1=Isodiametridae [[File:Isodiametra pulchra.jpg|60x60px]] |2={{clade |label1= |1=Dakuidae |label2=Aberrantospermata |2={{clade |label1= |1=Convolutidae [[File:Convolutriloba retrogemma underside on aquarium glass Length 3mm.jpg|60px]] |2=Mecynostomidae }} }} }} }} }} }} }} |label2=Nemertodermatida |2={{clade |label1=Ascopariidae |1={{clade |label1= |1=''Ascoparia'' |2=''Flagellophora'' [[File:Flagellophora sp.png|60px]] }} |label2=Nemertodermatidae |2={{clade |label1= |1=''Nemertoderma'' |state2=dashed |2=''Nemertinoides'' [[File:Nemertinoides elongatus.png|60x60px]] |3={{clade |label1= |1=''Meara stichopi'' [[File:Meara stichopi.jpg|60px]] |2=''Sterreria'' [[File:Sterreria variabilis.png|60x60px]] }} }} }} }} }} }} ==References== [[Wikipedia:Xenacoelomorpha]] f8g5dg7cj4vll8shte3oeflgra2w62b 6 332300 2835378 2026-10-01T20:14:22Z Young1lim 21186 {{Information |Description=Copilot: File Control B. 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Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} == Licensing == {{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} oa1tilxpc5ewl4qpz5bv4gw1l0yq0mt 0 332308 2835420 2026-10-02T02:34:23Z Howie2024 2995240 Create Time-Loop UFO/UAP Hypothesis article first draft. 2835420 wikitext text/x-wiki {{Research project}} = Time-Loop UFO/UAP Hypothesis = '''Version 1.0 — October 2026''' == Overview == The '''Time-Loop UFO/UAP Hypothesis''' is a speculative research hypothesis exploring whether some apparently anomalous observations could, in principle, be modeled as part of a self-consistent temporal information loop. The hypothesis does '''not''' propose that unidentified anomalous phenomena (UAP) are extraterrestrial spacecraft, future spacecraft, time machines, or evidence of time travel. No such conclusion is established by current scientific evidence. Instead, the hypothesis asks a more limited theoretical question: ''If a future information-processing system could somehow interact with information associated with an earlier period of history, could the resulting information and observations be modeled as part of a self-consistent causal or informational loop?'' The hypothesis is particularly concerned with the possibility that future artificial intelligence (AI), sensing systems, or augmented-reality (AR) technologies could introduce additional layers between a physical event and the information ultimately perceived or interpreted by a human observer. The purpose of this page is therefore to explore a conceptual model, not to establish that temporal loops or future-origin information actually occur. == Scientific Starting Point == The hypothesis draws conceptually on established research concerning causality, closed timelike curves (CTCs), and self-consistency. In general relativity, certain mathematical spacetime solutions contain closed timelike curves. A CTC is a timelike path that returns to an earlier event in its own causal history. Friedman et al. (1990) examined the Cauchy problem in spacetimes containing closed timelike curves and proposed that, if such curves were physically permitted, a local solution would need to be extendable into a globally self-consistent solution. This provides an important theoretical background for discussions of self-consistency in spacetimes containing CTCs. [https://doi.org/10.1103/PhysRevD.42.1915 Friedman et al. (1990)] Echeverria, Klinkhammer, and Thorne (1991) studied a classical billiard-ball model involving a wormhole and closed timelike curves. Their analysis found multiple self-consistent solutions for some initial trajectories. This demonstrates that self-consistency can be studied mathematically without establishing that physical time machines exist. [https://doi.org/10.1103/PhysRevD.44.1077 Echeverria, Klinkhammer & Thorne (1991)] The present hypothesis uses these ideas only as a theoretical foundation. It does not assume that closed timelike curves exist in nature. == UAP as an Observational Category == The term '''UAP''' is used for observations that cannot, at the time of reporting or analysis, be identified as aircraft or known natural phenomena. NASA has emphasized that the currently available number of high-quality UAP observations is limited and that this limitation prevents firm scientific conclusions about the nature of such events. NASA's UAP work emphasizes the importance of scientific data, appropriate instrumentation, calibration, and analysis. [https://science.nasa.gov/uap/faqs/ NASA UAP Frequently Asked Questions] This distinction is essential to the present hypothesis: * '''Unidentified''' does not mean extraterrestrial. * '''Unexplained''' does not mean physically impossible. * An unusual observation does not by itself demonstrate time travel. * An interpretation of an image is not necessarily identical to the physical event that produced the image. The hypothesis therefore begins with the observational status of UAP rather than with an assumed explanation. == Observation, Information, and Interpretation == A central feature of this hypothesis is the distinction between an event and the information produced about that event. A simplified observational chain can be represented as: <math> \text{Physical event} \rightarrow \text{Sensor} \rightarrow \text{Recorded data} \rightarrow \text{Processing} \rightarrow \text{Interpretation} \rightarrow \text{Human perception} </math> Each stage can introduce uncertainty. For example, an apparent motion in an image may depend on sensor position, viewing geometry, exposure characteristics, atmospheric conditions, image processing, or incomplete metadata. Consequently, an anomalous interpretation should not automatically be treated as an anomalous physical event. This distinction is especially important when artificial intelligence is used to enhance, classify, reconstruct, or interpret observational data. == Artificial Intelligence as an Information Layer == An advanced AI system could potentially operate between raw observations and human interpretation. A generalized information chain might therefore be: <math> \text{Physical event} \rightarrow \text{Sensor data} \rightarrow \text{AI processing} \rightarrow \text{Model output} \rightarrow \text{Human interpretation} </math> The AI output could contain useful information while still being an interpretation rather than a direct representation of the underlying physical event. This creates an important research question: '''How can an observer distinguish information contained in an observation from information introduced by the system interpreting the observation?''' This question does not require time travel. It is already relevant to contemporary AI-assisted image and video analysis. == Augmented Reality and the Information Layer == Augmented reality (AR) provides an additional conceptual layer. AR can be understood as technology that overlays digital information onto a user's view of the physical world. NIST describes AR as an enhanced version of reality created by overlaying digital information on an image of something being viewed through a device. [https://www.nist.gov/publications/augmented-reality-ar-usability-evaluation-framework-case-public-safety-communications NIST AR Usability Evaluation Framework] A simplified AR information chain can therefore be represented as: <math> \text{Physical world} \rightarrow \text{Sensors} \rightarrow \text{AI or software processing} \rightarrow \text{Digital information} \rightarrow \text{AR display} \rightarrow \text{Human perception} \rightarrow \text{Human action} </math> This creates an important distinction between: * what physically exists; * what a sensor detects; * what a computer infers; * what an AR system displays; and * what a human believes is being observed. The presence of an AR layer would therefore make interpretation more complex, not less. == The Temporal Information Feedback Hypothesis == The speculative extension begins by considering a hypothetical future information system. Suppose, purely as a thought experiment, that a future AI system possessed information about an event occurring at an earlier time. If that information could somehow be presented to a person in the earlier period through an AR system, the person's actions could potentially become part of the historical record. The conceptual sequence would then be: <math> I_{\text{future}} \rightarrow AR_{\text{past}} \rightarrow A_{\text{past}} \rightarrow H_{\text{history}} \rightarrow I_{\text{future}} </math> where: * <math>I_{\text{future}}</math> represents information available to a future system; * <math>AR_{\text{past}}</math> represents the hypothetical presentation of information through an AR system in the past; * <math>A_{\text{past}}</math> represents actions influenced by that information; * <math>H_{\text{history}}</math> represents the resulting historical record. The resulting information could then become part of the historical data available to the future system. This would constitute a hypothetical '''temporal information feedback loop'''. No such loop has been established experimentally. == From Temporal Information to a UAP Hypothesis == The UFO/UAP component of the hypothesis asks whether an apparently anomalous observation could, under a hypothetical temporal-information model, be associated with such a loop. The question is not: ''Are UAPs time travelers?'' Instead, the more limited question is: ''Could an apparently anomalous observation, if future evidence eventually demonstrated that it contained information or technology originating from a future period, be modeled as part of a self-consistent temporal information loop?'' This formulation deliberately postpones the question of origin. An observation could initially remain unexplained while alternative hypotheses are investigated, including: # known aircraft or other human technology; # atmospheric or astronomical phenomena; # sensor artifacts; # viewing geometry; # errors in measurement or interpretation; # image or video processing effects; # incomplete metadata; # conventional technological explanations not initially recognized; and # genuinely unexplained phenomena. A temporal explanation would therefore require substantially stronger evidence than simply observing something unusual. == Self-Consistency and the Time-Loop Hypothesis == If a temporal information loop were assumed for the purpose of a theoretical model, the loop would need to remain self-consistent. A simplified representation is: <math> S^{*}=\Phi(S^{*}) </math> where <math>S^{*}</math> represents a hypothetical self-consistent state or history and <math>\Phi</math> represents the collection of constraints defining the hypothetical loop. This notation is a mathematical analogy used in the present research project. It is not presented as an established equation governing UAP or time travel. The conceptual sequence would be: '''Possible event → information transfer → action → historical record → future information → consistency constraint''' The central question is whether the complete sequence could remain mutually compatible. == Information Integrity == The concept of '''information integrity''' is particularly important to this hypothesis. If information from a hypothetical future were introduced into the past, several questions would arise: # How could the origin of the information be established? # How could the information be distinguished from an AI-generated prediction? # How could an observer determine whether an AR display represented a physical observation or a model-generated interpretation? # How would the historical record preserve the distinction? # Could the information create the conditions that later caused the future system to possess that same information? These questions are related to causal consistency but are not themselves established consequences of general relativity. They constitute proposed research questions for an interdisciplinary model. == The Bootstrap Information Problem == A temporal information loop could produce a version of the well-known bootstrap problem. Suppose a future system possesses information about an earlier event. That information is transmitted, directly or indirectly, into the earlier period. People act on the information. The resulting events are recorded. The future system later obtains the information from those historical records. The apparent question then becomes: '''Where did the information originally come from?''' A schematic representation is: <math> I \rightarrow H \rightarrow I </math> where <math>I</math> represents information and <math>H</math> represents the historical record. Such a loop would not necessarily contain a conventional contradiction. However, it would raise questions about the origin, preservation, and physical realization of information. The existence of such a loop is hypothetical. == UAP Observation Versus UAP Interpretation == An important methodological principle is to maintain separate levels of description. '''Level 1 — Observation''' What was directly measured or recorded? '''Level 2 — Description''' What does the recording objectively show? '''Level 3 — Processing''' What transformations, enhancement, classification, or reconstruction were applied? '''Level 4 — Interpretation''' What explanations are consistent with the available evidence? '''Level 5 — Hypothesis''' What broader models could potentially explain the observation? A temporal-loop explanation belongs at Level 5. It should not be inserted into Level 1 or Level 2 merely because an observation appears unusual. == Relationship to Augmented Reality == AR introduces an additional methodological problem because the displayed scene can contain both physical and digital information. Conceptually: <math> R_{\text{display}} = R_{\text{physical}} + I_{\text{digital}} </math> where <math>R_{\text{display}}</math> represents the user's displayed perceptual environment, <math>R_{\text{physical}}</math> represents information derived from the physical environment, and <math>I_{\text{digital}}</math> represents digitally generated or retrieved information. This equation is a conceptual representation rather than a physical law. If the digital information were generated by an AI system, the observer could potentially perceive an object, annotation, prediction, reconstruction, or other representation that is not identical to a directly observed physical object. Therefore, an AR-mediated observation would require careful preservation of the underlying sensor data and metadata before conclusions were drawn about the physical phenomenon. == A Possible Temporal AR Loop == The strongest version of the hypothesis can be represented conceptually as: <math> H_t \rightarrow AI_{t+1} \rightarrow AR_t \rightarrow A_t \rightarrow H_t </math> where: * <math>H_t</math> represents historical information at time <math>t</math>; * <math>AI_{t+1}</math> represents a hypothetical future information-processing system; * <math>AR_t</math> represents information presented to hniv7w8tinndcm4b1r52olzkjxdrh13 2835422 2835420 2026-10-02T02:54:55Z Howie2024 2995240 Corrected version 1.1 updated 2835422 wikitext text/x-wiki {{Research project}} = Time-Loop UFO/UAP Hypothesis = '''Version 1.1 — October 2026''' == Overview == The '''Time-Loop UFO/UAP Hypothesis''' is a speculative interdisciplinary research framework examining whether an apparently anomalous observation could, in a hypothetical scenario, become part of a self-consistent loop involving information, artificial intelligence (AI), augmented reality (AR), human action, and historical records. The hypothesis does '''not''' propose that unidentified anomalous phenomena (UAP) are extraterrestrial spacecraft, time travelers, future spacecraft, or evidence of backward time travel. Instead, UAP are treated here as an '''observational category''': observations that have not yet been satisfactorily identified. The central question of this article is therefore narrower: '''If future-origin information were ever independently demonstrated, could it be modeled as part of a self-consistent temporal information loop?''' This is a hypothetical question, not an established scientific claim. The framework builds a conceptual bridge between: * UAP observation; * sensor data; * information processing; * artificial intelligence; * augmented reality; * human interpretation and action; * historical information; * causal feedback; * closed timelike curves; * the Novikov self-consistency principle; and * the broader research framework developed in [[Temporal Consistency and Quantum Ethics: 2001 as a Fictional Analogue]]. The article distinguishes among three levels of discussion: * '''Established science''' — established methods and findings concerning observation, information systems, artificial intelligence, augmented reality, causality, and theoretical physics. * '''Theoretical models''' — mathematical and physical models involving closed timelike curves, self-consistency, retrocausality, and information. * '''Speculative hypotheses''' — proposed extensions concerning future-origin information, UAP, AI, AR, and temporal information loops. The speculative portions of this article should not be interpreted as evidence that such phenomena exist. == Relationship to the Main Research Framework == This article is a supporting component of the broader research project developed in [[Temporal Consistency and Quantum Ethics: 2001 as a Fictional Analogue]]. The main article develops a general framework connecting: * temporal consistency; * causality; * information integrity; * artificial intelligence; * augmented reality; and * ethical constraints. The present article develops a more specific observational branch of that framework. The conceptual progression can be represented as: <math> \text{physical event} \rightarrow \text{sensor observation} \rightarrow \text{recorded data} \rightarrow \text{AI processing} \rightarrow \text{interpretation} \rightarrow \text{human action} \rightarrow \text{historical information} </math> The speculative temporal extension is: <math> I_{\mathrm{future}} \rightarrow AR_{\mathrm{past}} \rightarrow A_{\mathrm{past}} \rightarrow H_{\mathrm{history}} \rightarrow I_{\mathrm{future}} </math> This article therefore asks whether a hypothetical temporal information loop could be studied using the same concepts of physical consistency, informational consistency, provenance, causal minimalism, and ethical consistency developed in the main research framework. == Background == === UAP as an Observational Category === The term '''unidentified anomalous phenomena''' refers to observations that remain unidentified after available information and analysis have been considered. The term does not itself specify a cause. A UAP observation may potentially result from: * an aircraft or other conventional human technology; * atmospheric phenomena; * astronomical objects; * sensor artifacts; * optical effects; * viewing geometry; * motion of the observing platform; * image or video-processing effects; * incomplete or inaccurate metadata; * unfamiliar but conventional technology; * limitations in observation or measurement; or * phenomena that remain unexplained after available evidence has been examined. Consequently: <math> \text{unidentified observation} \neq \text{identified cause} </math> and: <math> \text{unexplained} \neq \text{evidence for time travel} </math> This distinction is fundamental to the present hypothesis. === Causality and Temporal Consistency === Ordinary physical reasoning assumes that causes precede their effects within the relevant causal structure. Relativity distinguishes timelike, null, and spacelike relationships between events. General relativity admits mathematical spacetime solutions containing closed timelike curves under certain conditions. A closed timelike curve is a worldline that returns to an earlier event in the spacetime description. The existence of such mathematical solutions does not establish that usable time travel occurs in nature. Research concerning closed timelike curves has nevertheless raised an important theoretical question: '''If a causal loop existed, what restrictions would be required for the complete history to remain physically consistent?''' The Novikov self-consistency principle is one proposed answer. In its basic form, a local physical solution involving a closed timelike curve must be extendable into a globally self-consistent solution. This provides a theoretical foundation for examining hypothetical information loops without assuming that arbitrary changes to the past are possible. === Information and Self-Consistency === A temporal paradox can be considered not only in terms of physical objects but also in terms of information. Suppose a hypothetical system received information from a future state and that information influenced events in an earlier state. If those earlier events subsequently contributed to the future state that generated the original information, a feedback loop could arise: <math> I_{\mathrm{future}} \rightarrow S_{\mathrm{past}} \rightarrow H_{\mathrm{history}} \rightarrow I_{\mathrm{future}} </math> The important question would then be whether the complete information history is self-consistent. This does not establish that such a loop can occur. It provides a mathematical and conceptual structure in which such a possibility could be examined. == From Observation to Interpretation == A central methodological distinction in this research is the difference between an observation and an interpretation. A simplified observation pipeline is: <math> O \rightarrow D \rightarrow P \rightarrow I \rightarrow H </math> where: * <math>O</math> = physical occurrence; * <math>D</math> = sensor data; * <math>P</math> = processing; * <math>I</math> = interpretation; and * <math>H</math> = human understanding or hypothesis. Each stage can introduce uncertainty. For example, a camera does not directly record an object's complete physical state. It records signals produced by an imaging system under particular exposure, optical, geometric, atmospheric, and instrumental conditions. Processing can then modify the representation. AI can classify, enhance, reconstruct, interpolate, summarize, or otherwise transform the information. Human observers subsequently interpret the resulting representation. Therefore: <math> \text{observation} \neq \text{description} \neq \text{processing} \neq \text{interpretation} \neq \text{hypothesis} </math> This distinction becomes especially important when AI-generated or AI-enhanced imagery is involved. An apparently unusual image may represent: * a physical phenomenon; * a sensor artifact; * a processing artifact; * an AI-generated reconstruction; * an AI classification; * a combination of physical and synthetic information; or * an interpretation imposed upon incomplete data. A scientifically useful investigation should preserve these distinctions. == Artificial Intelligence as an Information Layer == Modern information systems can transform observations into increasingly complex representations. A simplified AI pipeline may be expressed as: <math> D_{\mathrm{sensor}} \rightarrow M_{\mathrm{AI}} \rightarrow R_{\mathrm{AI}} \rightarrow H_{\mathrm{human}} </math> where: * <math>D_{\mathrm{sensor}}</math> is sensor data; * <math>M_{\mathrm{AI}}</math> is an AI model or processing system; * <math>R_{\mathrm{AI}}</math> is the resulting representation, classification, prediction, or reconstruction; and * <math>H_{\mathrm{human}}</math> represents human interpretation. AI therefore creates an additional information layer between physical measurement and human understanding. The distinction between raw measurement and processed representation becomes increasingly important when an observation is used to support a claim about an unusual physical event. This produces an important research question: '''How can an observer distinguish information contained in an observation from information introduced by the system interpreting the observation?''' This question does not require time travel. It is already relevant to contemporary AI-assisted image and video analysis. == Augmented Reality and the Information Layer == Augmented reality combines information generated by a digital system with a user's perception of a physical environment. A simplified AR information pathway can be written as: <math> W \rightarrow S \rightarrow D \rightarrow A \rightarrow P \rightarrow H </math> where: * <math>W</math> = physical world; * <math>S</math> = sensors; * <math>D</math> = digital information; * <math>A</math> = augmented-reality overlay; * <math>P</math> = human perception; and * <math>H</math> = human action or interpretation. AR therefore introduces an important distinction between: '''what is physically present''' and: '''what the information system tells the observer about what is physically present'''. The presence of an AR layer would therefore make interpretation more complex, not less. == The AI and AR Feedback System == AI and AR can be considered together as an information-processing system: <math> \text{physical world} \rightarrow \text{sensors} \rightarrow \text{AI processing} \rightarrow \text{digital information} \rightarrow \text{AR display} \rightarrow \text{human perception} \rightarrow \text{human action} </math> Human action can then produce new physical observations. This creates an ordinary feedback structure: <math> \text{information} \rightarrow \text{human action} \rightarrow \text{new observation} \rightarrow \text{new information} </math> Nothing about this ordinary feedback loop requires time travel. It is already a characteristic of many information systems. The significance for the present hypothesis is that the same structure provides a conceptual pathway through which a hypothetical temporal information loop could be represented. == The Time-Loop UAP Hypothesis == The hypothesis can be stated conservatively: '''If a future information-processing system could somehow provide information to an earlier historical period, and if that information influenced observations or actions that later contributed to the future system's own informational state, the resulting process could be modeled as a temporal information loop.''' The hypothesis does not require that the information arrive through a physical spacecraft. It could, in principle, be represented as: * an image; * a measurement; * a prediction; * a coordinate; * a symbolic message; * an AI-generated representation; * an AR overlay; or * another information-bearing signal. The crucial hypothetical property would be its '''temporal provenance'''. The question would not simply be: '''Was a UAP observed?''' Instead, it would be: '''Can the information associated with the observation be demonstrated to have originated from a future state of the same causal system?''' That is a much stronger requirement. No presently established UAP evidence demonstrates this. == Temporal Information Feedback == The central proposed feedback structure is: <math> I_{\mathrm{future}} \rightarrow AR_{\mathrm{past}} \rightarrow A_{\mathrm{past}} \rightarrow H_{\mathrm{history}} \rightarrow I_{\mathrm{future}} </math> where: * <math>I_{\mathrm{future}}</math> = hypothetical future-origin information; * <math>AR_{\mathrm{past}}</math> = an augmented-reality or information display in the past; * <math>A_{\mathrm{past}}</math> = human action influenced by that information; and * <math>H_{\mathrm{history}}</math> = the resulting historical record. The resulting information could then become part of the historical data available to the future system. This would constitute a hypothetical '''temporal information feedback loop'''. No such loop has been established experimentally. == From Temporal Information to a UAP Hypothesis == The UAP component of the hypothesis asks whether an apparently anomalous observation could, under a hypothetical temporal-information model, be associated with such a loop. The question is not: '''Are UAPs time travelers?''' Instead, the more limited question is: '''Could an apparently anomalous observation, if future evidence eventually demonstrated that it contained information or technology originating from a future period, be modeled as part of a self-consistent temporal information loop?''' This formulation deliberately postpones the question of origin. An observation could initially remain unexplained while alternative hypotheses are investigated, including: # known aircraft or other human technology; # atmospheric or astronomical phenomena; # sensor artifacts; # viewing geometry; # errors in measurement or interpretation; # image or video processing effects; # incomplete metadata; # conventional technological explanations not initially recognized; and # genuinely unexplained phenomena. A temporal explanation would therefore require substantially stronger evidence than simply observing something unusual. == Physical, Informational, and Interpretive Consistency == The broader research framework distinguishes several types of consistency. === Physical consistency === A hypothetical temporal process would have to satisfy whatever physical laws govern the relevant spacetime. If closed timelike curves were involved, this could include global self-consistency constraints. === Informational consistency === The information appearing at different points in the loop would have to remain mutually compatible. If a future system received a historical record containing information that originated from that future system, the complete information history would need to be examined for consistency. === Interpretive consistency === The interpretation of an observation must remain distinguishable from the underlying measurement. An AI or AR system could alter what an observer perceives without altering the underlying physical event. Therefore: <math> \text{physical event} \neq \text{sensor representation} \neq \text{AI representation} \neq \text{human interpretation} </math> === Ethical consistency === If a future information system could influence historical human decisions, ethical constraints would become relevant. A hypothetical system with access to causally sensitive historical information would raise questions concerning: * information integrity; * unnecessary intervention; * consent; * manipulation; * historical authenticity; * unintended consequences; * accountability; and * preservation of human agency. This connects directly to the broader framework developed in [[Temporal Consistency and Quantum Ethics: 2001 as a Fictional Analogue]]. == A Proposed Framework == The following principles are proposed as a conceptual framework. They are not established physical laws. === 1. Information integrity === Measurements, metadata, processing steps, and interpretations should be preserved separately. A future investigation should ideally retain: * original sensor files; * calibration information; * timestamps; * sensor location; * sensor orientation; * exposure information; * instrument characteristics; * processing history; * AI-model information; * transformation records; and * human annotations. === 2. Causal minimalism === If a system had access to causally sensitive information, it should minimize unnecessary intervention. Conceptually: <math> \text{unnecessary intervention} \rightarrow \text{additional causal pathways} \rightarrow \text{greater feedback complexity} </math> In a hypothetical temporal system, minimizing unnecessary intervention could reduce opportunities for unstable or contradictory information loops. === 3. Provenance preservation === Every significant information object should have a traceable origin. For a UAP investigation, this means distinguishing: <math> P_{\mathrm{physical}} \rightarrow P_{\mathrm{sensor}} \rightarrow P_{\mathrm{processing}} \rightarrow P_{\mathrm{AI}} \rightarrow P_{\mathrm{interpretation}} </math> The purpose is to determine which portions of the final representation can be traced to physical measurement and which are products of later processing. === 4. Predictive transparency === A system should distinguish between information that describes an event and information that may influence the event. This distinction becomes important when predictions are shown to people through AI systems or AR displays. The ordinary feedback structure is: <math> \text{prediction} \rightarrow \text{behavior} \rightarrow \text{new data} \rightarrow \text{prediction} </math> A hypothetical temporal system would extend this into: <math> \text{prediction} \rightarrow \text{future action} \rightarrow \text{historical intervention} \rightarrow \text{changed data} \rightarrow \text{prediction} </math> === 5. Self-consistency === If a temporal information loop were ever demonstrated, the complete information history would need to be evaluated rather than examining isolated events. Conceptually: <math> H_{\mathrm{complete}} \in C_{\mathrm{physical}} \cap C_{\mathrm{informational}} \cap C_{\mathrm{interpretive}} \cap C_{\mathrm{ethical}} </math> where the four sets represent different admissibility conditions. This extends the idea of self-consistency into an interdisciplinary framework. == A Possible Temporal AR Loop == A particularly interesting thought experiment involves AR. Imagine that a future information-processing system possesses highly detailed historical information. Suppose, hypothetically, that the system somehow provides a representation of an event to an observer in an earlier period. The observer sees the information through an AR system. The observer then acts on that information. The action becomes part of the historical record. The future system subsequently learns from that historical record. The conceptual loop is: <math> I_F \rightarrow AR_P \rightarrow A_P \rightarrow H \rightarrow AI_F \rightarrow I_F </math> where: * <math>I_F</math> = future information; * <math>AR_P</math> = past AR representation; * <math>A_P</math> = past action; * <math>H</math> = historical record; and * <math>AI_F</math> = future AI system. This is a thought experiment. It does not establish that such a mechanism exists. == Bootstrap Information and the Origin Problem == A classic information-loop problem arises when information exists in a causal loop without an identifiable external origin. For example: <math> I_1 \rightarrow I_2 \rightarrow I_3 \rightarrow I_1 </math> If the information contained in <math>I_1</math> is completely determined by later information in the same loop, it may become difficult to identify an independent source for the information. This does not automatically constitute a contradiction. However, it creates a major epistemological problem. A scientific investigation would need to distinguish: * information genuinely originating from an external source; * information generated internally by the system; * information reconstructed from incomplete observations; * information introduced by human interpretation; * information produced by AI systems; and * information that only appears to have a future origin because its provenance is incomplete. The bootstrap problem therefore makes provenance especially important. == UAP Observation Versus UAP Interpretation == The framework proposes maintaining separate levels of description. '''Level 1 — Observation''' What was directly measured or recorded? '''Level 2 — Description''' What does the recording objectively show? '''Level 3 — Processing''' What transformations, enhancement, classification, or reconstruction were applied? '''Level 4 — Interpretation''' What explanations are consistent with the available evidence? '''Level 5 — Hypothesis''' What broader models could potentially explain the observation? A temporal-loop explanation belongs at Level 5. It should not be inserted into Level 1 or Level 2 merely because an observation appears unusual. == Relationship to Augmented Reality == AR introduces an additional methodological problem because the displayed scene can contain both physical and digital information. Conceptually: <math> R_{\mathrm{display}} = R_{\mathrm{physical}} + I_{\mathrm{digital}} </math> where: * <math>R_{\mathrm{display}}</math> represents the displayed perceptual environment; * <math>R_{\mathrm{physical}}</math> represents information derived from the physical environment; and * <math>I_{\mathrm{digital}}</math> represents digitally generated or retrieved information. This equation is a conceptual representation rather than a physical law. If the digital information were generated by an AI system, the observer could potentially perceive an object, annotation, prediction, reconstruction, or other representation that is not identical to a directly observed physical object. Therefore, an AR-mediated observation would require careful preservation of the underlying sensor data and metadata before conclusions were drawn about the physical phenomenon. == Information Provenance and Historical Integrity == The hypothesis requires unusually strong attention to provenance. For an information object <math>I</math>, provenance can be represented conceptually as: <math> \Pi(I) = \{t,s,m,p,a,r\} </math> where: * <math>t</math> = timestamp; * <math>s</math> = source; * <math>m</math> = metadata; * <math>p</math> = processing history; * <math>a</math> = analytical actions; and * <math>r</math> = resulting representation. A temporal-origin claim would require showing that the provenance chain cannot be explained by ordinary forward information flow. This is a much stronger requirement than demonstrating that a prediction happened to be correct. == What Would Count as Evidence? == The Time-Loop UAP Hypothesis should require substantially stronger evidence than an unusual image or unexplained observation. Potentially relevant evidence would include: === 1. Independent physical measurement === The phenomenon should be recorded by calibrated instruments capable of producing quantitative measurements. === 2. Multiple synchronized observations === Independent sensors should observe the same event with synchronized timing. === 3. Complete metadata === The record should include sufficient information to reconstruct the observational circumstances. === 4. Preservation of original data === Original sensor data should be preserved rather than relying exclusively on screenshots, compressed video, or later reconstructions. === 5. Independent analysis === The observation should be analyzable by researchers who are not dependent upon the original interpretation. === 6. Demonstrable information provenance === If future-origin information is proposed, the information should have a demonstrable provenance that cannot be explained by ordinary information transfer. === 7. Temporal priority === The allegedly future-origin information would need to be demonstrably present before the event or information from which it would ordinarily have been derived. This is crucial. A prediction generated after an event cannot ordinarily establish that the information originated from the future. === 8. Reproducibility === The effect should be observable or testable independently. === 9. Falsifiable predictions === The hypothesis should produce predictions that distinguish it from competing explanations. === 10. Exclusion of conventional explanations === Sensor artifacts, atmospheric effects, astronomical objects, viewing geometry, image processing, human technology, and other ordinary explanations should be investigated before a temporal explanation is considered. == Alternative Explanations and Falsifiability == The hypothesis should remain subordinate to ordinary explanations until evidence requires otherwise. Potential explanations include: * conventional aircraft or technology; * atmospheric or astronomical phenomena; * sensor artifacts; * image-processing effects; * viewing-geometry effects; * AI interpretation; * AR-generated information; * incomplete metadata; * conventional informational feedback; and * genuinely unexplained phenomena. A temporal explanation would require evidence that distinguishes it from these alternatives. An unresolved observation therefore remains an unresolved observation until additional evidence establishes a specific explanation. == Mathematical Formulation == The equations in this section are proposed mathematical representations of the conceptual framework. They are not equations derived from quantum mechanics or established models of time travel. === State-transition representation === Let <math>S_t</math> represent the information state of a system at time <math>t</math>. An ordinary forward process can be represented as: <math> S_{t+1}=F_t(S_t,A_t) </math> where <math>A_t</math> represents actions or interventions at time <math>t</math>. A hypothetical temporally coupled system could be represented as: <math> S_t=G_t(S_{t-1},A_{t-1},S_{t+1},B_t) </math> where <math>B_t</math> represents additional boundary or environmental information. The future-state dependence is the speculative element. === Trajectory and fixed-point representation === A complete trajectory may be written: <math> S=(S_0,S_1,\ldots,S_T) </math> A self-consistent trajectory can be represented by: <math> S^{*}=\Phi(S^{*}) </math> This means that the complete history reproduces itself under the transformation and constraints represented by <math>\Phi</math>. This is a mathematical analogy rather than an established physical law. === Physical, informational, interpretive, and ethical admissibility === The proposed framework can be represented as: <math> S^{*} \in C_{\mathrm{physical}} \cap C_{\mathrm{informational}} \cap C_{\mathrm{interpretive}} \cap C_{\mathrm{ethical}} </math> A history would therefore be considered admissible in the model only if it satisfies all four classes of constraint. == Probability-Based State Transformations == A separate research question concerns whether constrained probability transformations can provide useful mathematical analogies for temporally constrained systems. Let: <math> p_t(x)\geq0 </math> and: <math> \sum_x p_t(x)=1 </math> where <math>p_t(x)</math> represents the probability of information state <math>x</math> at time <math>t</math>. A probabilistic transformation can be written as: <math> \widetilde{p}_{t+1}(x) = T_t(p_t,x) </math> If the transformed distribution is not normalized, define: <math> Z_{t+1} = \sum_x \widetilde{p}_{t+1}(x) </math> and: <math> p_{t+1}(x) = \frac{\widetilde{p}_{t+1}(x)} {Z_{t+1}} </math> This provides an abstract analogy: '''transformation → constraint → admissible state''' However, probability normalization alone is not equivalent to temporal consistency. Normalization ensures that a probability distribution sums to one. It does not ensure that a corresponding history is physically possible, informationally coherent, or ethically permissible. A trajectory-level admissibility condition can be represented as: <math> \mathcal{A}_{\mathrm{total}} = \mathcal{A}_{\mathrm{phys}} \cap \mathcal{A}_{\mathrm{info}} \cap \mathcal{A}_{\mathrm{interp}} \cap \mathcal{A}_{\mathrm{eth}} </math> where: * <math>\mathcal{A}_{\mathrm{phys}}</math> represents physically admissible trajectories; * <math>\mathcal{A}_{\mathrm{info}}</math> represents informationally consistent trajectories; * <math>\mathcal{A}_{\mathrm{interp}}</math> represents interpretation-consistent trajectories; and * <math>\mathcal{A}_{\mathrm{eth}}</math> represents ethically admissible trajectories. A constrained probability distribution could then be written conceptually as: <math> P_{\mathrm{adm}}(x) = P(x\mid x\in\mathcal{A}_{\mathrm{total}}) </math> This remains an abstract modeling analogy. It does not imply that ethical rules are physical laws or that quantum mechanics requires the proposed ethical constraints. == Relationship to Closed Timelike Curves == The hypothesis draws conceptual inspiration from research concerning closed timelike curves. In a spacetime containing a closed timelike curve, a worldline can in principle return to an earlier spacetime event. The important theoretical issue is whether a complete solution can remain self-consistent. Friedman, Morris, Novikov, Echeverria, Klinkhammer, Thorne, and Yurtsever examined the Cauchy problem in spacetimes containing closed timelike curves and discussed the need for a global self-consistency condition if such curves are permitted. Echeverria, Klinkhammer, and Thorne subsequently examined a classical billiard-ball model involving wormhole-generated closed timelike curves and found examples involving multiple self-consistent solutions. The Time-Loop UAP Hypothesis does not assert that UAP observations involve closed timelike curves. Instead, closed-timelike-curve research supplies a theoretical vocabulary for asking how a causal loop might remain globally consistent. == Relationship to the Novikov Self-Consistency Principle == The [[Novikov Self-Consistency Principle]] provides an especially relevant conceptual connection. The principle can be summarized as: <math> \text{local possibility} \rightarrow \text{global consistency requirement} \rightarrow \text{admissible history} </math> Applied only as a speculative analogy, the principle suggests that if a temporal information loop existed, not every apparently possible information sequence would necessarily correspond to an admissible history. The hypothesis therefore does not assume: '''The past can be changed arbitrarily.''' Instead it asks: '''If future-origin information existed, what global constraints would be required for the complete information history to remain self-consistent?''' This is a substantially narrower proposition. == Relationship to Temporal Consistency and Quantum Ethics == The strongest conceptual relationship is with [[Temporal Consistency and Quantum Ethics: 2001 as a Fictional Analogue]]. The main article identifies a progression: <math> \text{physical consistency} \rightarrow \text{informational consistency} \rightarrow \text{ethical consistency} </math> The present UAP hypothesis adds another layer: <math> \text{physical observation} \rightarrow \text{information} \rightarrow \text{interpretation} \rightarrow \text{action} \rightarrow \text{historical information} </math> The two frameworks can therefore be combined conceptually. A hypothetical future AI system might not need to physically transport an object through time. It would only need, in the speculative model, to affect information that later becomes part of its own historical input. This produces the possibility of: <math> \text{information} \rightarrow \text{action} \rightarrow \text{history} \rightarrow \text{future information} </math> The main article already considers a related structure involving augmented reality: '''AR information → human behavior → historical record → future training data''' The present article extends that conceptual structure into the UAP domain. The important distinction remains: '''ordinary informational feedback is already real; a temporal feedback loop remains hypothetical.''' == Ethical Implications of a Hypothetical Temporal Information System == If a future information-processing system could affect historical information, the ethical problem would extend beyond physics. A hypothetical system might face questions such as: * Should it intervene at all? * How much intervention would be justified? * Should it disclose the origin of information? * Could historical people give meaningful consent? * What happens if the information changes subsequent decisions? * Who is responsible for unintended consequences? * How should historical records be protected from deliberate manipulation? * Should an AI system be permitted to optimize outcomes by altering information conditions? These questions are consistent with the broader concept of '''ethical consistency''' developed in the main research article. The ethical framework does not depend on proving time travel. Similar questions already arise when AI systems influence human behavior and subsequently learn from the resulting behavior. == Science Fiction and Conceptual Analogies == Science fiction can provide useful conceptual analogies, but it should not be treated as scientific evidence. The broader research project uses [[Temporal Consistency and Quantum Ethics: 2001 as a Fictional Analogue]] to examine fictional representations of: * advanced AI; * information asymmetry; * autonomous decision-making; * objectives and constraints; * human-machine interaction; and * consequences of information systems. The present article does not claim that fictional depictions of UFOs or time travel predict physical reality. Fiction can instead serve as a conceptual laboratory in which questions concerning causality, information, AI, and temporal consistency can be examined. == Research Questions == The following questions remain open within the speculative framework: # Can UAP investigation methods be designed to preserve complete sensor and processing provenance? # How can AI-generated interpretations be distinguished from direct sensor measurements? # How should AR systems distinguish physical observations from digital overlays? # Can information-feedback loops be modeled using established causal and information-theoretic mathematics? # Under what assumptions can a temporal information loop be represented as a fixed-point problem? # What conditions would be required for a future-origin information claim to be empirically testable? # Could a future information system create a logically self-consistent information loop without producing an observable contradiction? # Would such a loop necessarily involve a physical closed timelike curve, or could a different theoretical mechanism produce an equivalent information structure? # How should bootstrap information be treated within a causal model? # What would distinguish a genuine temporal information effect from an ordinary prediction, coincidence, data leak, or reconstruction? # Could probability-based state transformations provide a useful mathematical language for studying constrained temporal information systems? # What ethical constraints would be appropriate for an information-processing system capable of influencing historical conditions? == Limitations and Open Questions == This article has substantial limitations. First, no established experiment demonstrates controllable communication from the future into the past. Second, no established evidence demonstrates that UAP are caused by time travel. Third, unexplained observations do not by themselves establish a new physical mechanism. Fourth, AI and AR can introduce additional layers of interpretation between a physical event and human perception. Fifth, the mathematical formulations in this article are proposed models and analogies rather than experimentally validated physical equations. Sixth, a self-consistent mathematical model does not demonstrate that the modeled process occurs in nature. Seventh, a correct prediction does not by itself establish future-origin information. Finally, the hypothesis may ultimately prove unfalsifiable or physically impossible if no mechanism exists by which future-origin information can influence past observations. These limitations are not weaknesses to be hidden; they are part of the scientific definition of the hypothesis. == Conclusion == The Time-Loop UAP Hypothesis proposes a conservative question rather than a conclusion. UAP are treated as observations rather than explanations. The research begins with a standard information pathway: <math> \text{physical event} \rightarrow \text{sensor} \rightarrow \text{data} \rightarrow \text{processing} \rightarrow \text{interpretation} </math> AI and AR introduce additional information-processing layers. An ordinary feedback system can then arise: <math> \text{prediction} \rightarrow \text{human action} \rightarrow \text{new data} \rightarrow \text{new prediction} </math> The speculative extension is: <math> \text{future-origin information} \rightarrow \text{past information system} \rightarrow \text{human action} \rightarrow \text{historical record} \rightarrow \text{future information} </math> If such a process were ever demonstrated, the concepts of physical consistency, informational consistency, interpretive integrity, provenance, and ethical consistency could provide a framework for analyzing it. The hypothesis therefore does not begin with the proposition that UAP are time travelers. It begins with a more general scientific question: '''Could future-origin information, if independently demonstrated, form part of a globally self-consistent information loop?''' At present, this remains a speculative research question. == References == === Physics and temporal consistency === * Friedman, J. L., Morris, M. S., Novikov, I. D., Echeverria, F., Klinkhammer, G., Thorne, K. S., and Yurtsever, U. (1990). "Cauchy problem in spacetimes with closed timelike curves." ''Physical Review D'', 42, 1915–1930. [https://doi.org/10.1103/PhysRevD.42.1915 DOI] * Echeverria, F., Klinkhammer, G., and Thorne, K. S. (1991). "Billiard balls in wormhole spacetimes with closed timelike curves: Classical theory." ''Physical Review D'', 44, 1077–1099. [https://doi.org/10.1103/PhysRevD.44.1077 DOI] * Hawking, S. W. (1992). "Chronology protection conjecture." ''Physical Review D'', 46, 603–611. [https://doi.org/10.1103/PhysRevD.46.603 DOI] * Deutsch, D. (1991). "Quantum mechanics near closed timelike lines." ''Physical Review D'', 44, 3197–3217. [https://doi.org/10.1103/PhysRevD.44.3197 DOI] === UAP methodology === * NASA. (2023). ''NASA Unidentified Anomalous Phenomena Independent Study Team Final Report''. [https://science.nasa.gov/uap/ NASA UAP Independent Study] === Artificial intelligence and information systems === * National Institute of Standards and Technology. (2023). ''Artificial Intelligence Risk Management Framework (AI RMF 1.0)''. [https://www.nist.gov/itl/ai-risk-management-framework NIST AI Risk Management Framework] * National Institute of Standards and Technology. ''AI Measurement and Evaluation''. [https://www.nist.gov/ai-measurement-and-evaluation NIST AI Measurement and Evaluation] === Augmented reality === * Azuma, R. T. (1997). "A Survey of Augmented Reality." ''Presence: Teleoperators and Virtual Environments'', 6(4), 355–385. [https://doi.org/10.1162/pres.1997.6.4.355 DOI] === Fiction and artificial intelligence === * Kubrick, S., director. (1968). ''2001: A Space Odyssey''. Metro-Goldwyn-Mayer. == Further Reading == * [[Closed Timelike Curves]] * [[Novikov Self-Consistency Principle]] * [[Causality]] * [[Temporal Consistency and Quantum Ethics: 2001 as a Fictional Analogue]] * [https://science.nasa.gov/uap/ NASA UAP Independent Study] * [https://www.nist.gov/itl/ai-risk-management-framework NIST AI Risk Management Framework] * [https://doi.org/10.1162/pres.1997.6.4.355 Azuma, "A Survey of Augmented Reality"] == Research Status == '''Research status: Speculative interdisciplinary framework.''' Version 1.1 develops a conceptual hypothesis connecting UAP observation, information provenance, artificial intelligence, augmented reality, temporal information feedback, causal consistency, and ethical constraints. The hypothesis does not claim that UAP are extraterrestrial spacecraft, time travelers, or evidence of backward time travel. No established scientific experiment currently demonstrates controllable information transfer from the future to the past. The mathematical formulations presented in this article are proposed models and analogies for further investigation. Future versions may refine the mathematical framework, develop computational simulations, examine information-theoretic constraints, and investigate whether the proposed temporal-information structures can produce experimentally distinguishable predictions. == Author and Attribution == This research article is part of an ongoing independent research project developed by Howard Richardson. The ideas presented here are exploratory and are intended to be developed, criticized, tested, refined, or rejected through further research. The publication of a speculative hypothesis on Wikiversity does not constitute scientific confirmation. The article is released for educational and research discussion under the applicable Wikiversity and Wikimedia licensing framework. 3j5mrw7f3f3uisc7ihrg78jj9ro82vf 14 332312 2835494 2026-10-02T11:05:37Z Dick Bos 24466 new subcat 2835494 wikitext text/x-wiki [[Category:Economics]] jmwu7okx9t13dj65jev6gp2p45qi1x2